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From the *Ann & Robert H. Lurie

Children’s Hospital of Chicago,

Chicago, Illinois; † Northwestern

University Feinberg School of

Medicine, Department of Pediatrics,

Chicago, Illinois.

Address correspondence to Suma Rao-

Gupta, MPH, MBA, Director, Pedersen

Family Learning Center and Health

Sciences Library, Clinical &

Organizational Development, Ann &

Robert H. Lurie Children’s Hospital of

Chicago, 225 E. Chicago Avenue, Box

47, Chicago, IL 60611-2991. E-mail:

[email protected]

Received July 7, 2017;

Revised October 13, 2017;

Accepted November 5, 2017.

1524-9042/$36.00

� 2017 by the American Society for Pain Management Nursing

https://doi.org/10.1016/

j.pmn.2017.11.002

Leveraging Interactive Patient Care Technology to Improve Pain Management Engagement

- - - Suma Rao-Gupta, MPH, MBA, *

David Kruger, MSN, RN, CNML,*

Lonna D. Leak, MS, BSN, RN, NE-BC,*

Lisa A. Tieman, BSN, RN, CPN,*

and Renee C. B. Manworren, PhD, APRN, BC, APN-PM,

FAAN *,†

- ABSTRACT: Background: Most children experience pain in hospitals; and their par-

ents report dissatisfaction with how well pain was managed. Engaging

patients and families in the development and evaluation of pain treat-

ment plans may improve perceptions of pain management and hospital

experiences. Objectives: The aim of this performance improvement

project was to engage patients and families to address hospitalized pe-

diatric patients’ pain using interactive patient care technology. The goal

was to stimulate conversations about pain management expectations

and perceptions of treatment plan effectiveness among patients, par-

ents, and health care teams. Methods: Plan-Do-Study-Act was used to

design, develop, test, and pilot new workflows to integrate the interac-

tive patient care technology system with the automated medication

dispensing system and document actions from both systems into the

electronic health record. Setting: The pediatric surgical unit and hema-

tology/oncology unit of a free-standing, university-affiliated, urban

children’s hospital were selected to pilot this performance improve-

ment project because of the high prevalence of pain from surgeries and

hematologic and oncologic diseases, treatments, and invasive proced-

ures. Results: Documentation of pain assessments, nonpharmacologic

interventions, and evaluation of treatment effectiveness increased. The

proportion of positive family satisfaction responses for pain manage-

ment significantly increased from fiscal year 2014 to fiscal year 2016

(p ¼ .006). Conclusion: By leveraging interactive patient care technolo- gies, patients and families were engaged to take an active role in pain

treatment plans and evaluation of treatment outcomes. Improved active

communication and partnership with patients and families can effec-

tively change organizational culture to be more sensitive to patients’

Pain Management Nursing, Vol 19, No 3 (June), 2018: pp 212-221

p ri n t &

w e b 4 C = F P O

213Interactive Patient Care Technology Improve Pain Management

pain and patients’ and families’ hospital experi-

ences.

� 2017 by the American Society for Pain Management Nursing

Parents play a vital role in children’s pain experiences

(Palermo, Valrie, & Karlson, 2014; Simons, Goubert,

Vervoort, & Borsook, 2016), and parents’ satisfaction

with children’s pain treatment is a key outcome measure for hospitals (McGrath et al., 2008). Because

more than 80% of hospitalized children experience

acute pain from their disease or injury, treatment,

and invasive procedures, including surgery

(Kozlowski et al., 2014; Solodiuk et al., 2014;

Walther-Larsen et al., 2017), it has been suggested

that parents’ involvement with management of pain

during children’s hospitalization will significantly reduce overall pain perception (Habich et al., 2012;

Simons, 2015). A focused effort is required for nurses

to engage and partner with parents to better identify,

acknowledge, and manage pain experiences of

hospitalized pediatric patients.

In fiscal year 2014, parents’ satisfaction with their

children’s pain treatment at Ann & Robert H. Lurie

Children’s Hospital of Chicago (Lurie Children’s) was not statistically different than those for other Chil-

dren’s Hospital Association (CHA) facilities. However,

FIGURE 1. - Proportion of positive responses to HCAHPS pain qu child’s pain?’’ Statistically significant difference p < .05. HCA viders and Systems; CHA ¼ Children’s Hospital Association FY15 ¼ fiscal year 2015; FY16 ¼ fiscal year 2016.

parents’ satisfaction was lower than desired (Fig. 1).

These survey results and an opportunity to leverage

technology to improve parents’ engagement in pain

treatment motivated the health care team to pursue

new methods to partner with parents to improve the

organization’s approach to pain management and hos-

pital experiences. The GetWellNetwork Pain Pathway was identified

as a potential conduit to strengthen effective collabora-

tion with parents to better manage hospitalized chil-

dren’s pain. Therefore, the aim of this performance

improvement project was to implement an engage-

ment initiative to address pain in hospitalized pediatric

patients using GetWellNetwork interactive patient care

technology (IPC). The goal was to stimulate conversa- tions about pain management expectations and per-

ceptions of the effectiveness of treatment plans

among patients, parents, and health care teams.

METHODS

The Plan-Do-Study-Act performance improvement

model was used to design, develop, test, and pilot

new pain assessment workflows. IPC uses the patient’s

bedside television to deliver interactive educational

and entertainment content. Content includes both,

clinical tools that allow bedside staff to order targeted health education and launch IPC pathways, and

estion: ‘‘Did staff do everything they could to manage your HPS ¼ Hospital Consumer Assessment of Healthcare Pro- benchmark; FY14 ¼ fiscal year 2014, baseline measure;

p ri n t &

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214 Rao-Gupta et al.

entertainment options, such as movies, internet, video

games, and streaming music options (Kompany, Luis,

Manganaro, Motacki, Mustacchio, & Provenzano,

2016).

Setting Two inpatient units, the Pediatric Surgical and Solid Or-

gan Transplant Unit (Pediatric Surgical Unit) and the Hematology/Oncology and Transplantation Unit (He-

matology/Oncology Unit), were identified as pilot

units for this performance improvement project. These

units were selected because of the high prevalence of

pain from surgeries and hematologic and oncologic dis-

eases, treatment, and invasive procedures. The Pediat-

ric Surgical Unit has 48 beds with an average daily

census of 33 patients. The Hematology/Oncology Unit has 24 beds with an average daily census of 20.5

patients. Staffing ratios for both units vary by patient

acuity but are budgeted for one registered nurse for

every three patients (1:3).

Project Team The core project team included representatives from

nursing, patient-family education, information technol-

ogy, nursing informatics, pharmacy, and our IPC vendor, GetWellNetwork. Members of each unit’s lead-

ership, including nurse educators and pain manage-

ment champions, were key members of the project

team. This multidisciplinary project team met weekly

to discuss workflows, logistics, and the information

technology build. Staff who had a passion for pain man-

agement, technology, and improving the patient and

FIGURE 2. - Workflow redesign illustrating AMD & EHR integrati dispensing system; EHR ¼ electronic health record; RN ¼ regi technology. Copyright �2017, GetWellNetwork Inc. Reproduce

family experience championed this effort and

informed colleagues about the new workflows.

Workflow and Pathway Development The project team decided methods to stimulate discus-

sion and better communicate the organization’s commit-

ment to partner with patients and families to address

pain were needed. Direct care nurses were identified

as the primary health care providers to engage families

in pain management. At Lurie Children’s, direct care nurses coordinate care and play an integral role in part-

nering with patients, families, and the multidisciplinary

health care team from admission to discharge.

Admission Pain Pathway. The project team identi- fied the time of admission as critical for initiating part-

nerships with patients and families, and direct care

nurses identified the need to make pain management

a priority for care on admission (Fig. 2). Two questions were added to the inpatient admission assessment tool

for the nurse to ask the parent/caregiver (Table 1).

Once the admission assessment is completed, pa-

tients and families are required to watch two videos to

access entertainment options. The first video focuses

on patient safety and orientation to the hospital stay.

The second video, ‘‘Partnering in Pain,’’ explains the

hospital’s commitment to pain management. This 90- second video was created by direct care nurses to

inform patients and families of the desire and goal to

partner to address pain. The video is available in En-

glish and Spanish. The video provides a mechanism

to assist direct care nurses to discuss with patients

and families pain management expectations, assess-

ment strategies, interventions, and preferences.

on with GetWellNetworkTM. AMD ¼ automated medication stered nurse; Rx ¼ prescription; HIT ¼ health information d with permission.

TABLE 1.

Added Admission Assessment Questions and Rationale for Added Questions

Question Rationale

Question 1: At Lurie Children’s we want to do all that we can to provide comfort and relieve pain for our patients. Have you discussed pain management with the patient or caregiver?

This question serves as a prompt for the nurse to start a conversation with the patient and parent and/or guardian. This question helps the caregiver establish a conversation regarding pain management at the time of admission.

Question 2: What things have helped you (patient) or your child’s (parent) pain management in the past?

This question helps the health care team incorporate methods identified to relieve and cope with pain into the patient’s care plan.

p ri n t & w e b 4 C = F P O

215Interactive Patient Care Technology Improve Pain Management

Ongoing Bedside Communication. Each patient room has a whiteboard with one area specifically de-

signed to document the patient’s pain plan (Fig. 3). Pa- tient and parent responses to admission assessment

questions are transferred onto the whiteboard. This in-

formation is then readily available to all health care

team members, as well as the patient and family. The

goal of the whiteboard is to facilitate communication

of the pain plan and to serve as a reminder to the pa-

tient, family, and members of the health care team

regarding how to intervene to manage the patient’s

FIGURE 3. - Photos of whiteboards in patient rooms. Patient- section.

pain or what has been done to address the patient’s

pain. It facilitates continued communication regarding

how to address pain and pain control at the bedside.

Daily Leadership Rounds. The leadership of the pi- lot units defined their role as promoting conversations

with patients, families and health care teams related to

pain and the effectiveness of pain management plans. They identified the need to endorse daily communica-

tion about pain to foster an organizational culture sen-

sitive to patients’ pain and hospital experiences. The

pilot units’ leadership teams began including questions

specific information is documented under the Pain Plan

p ri n t &

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FIGURE 4. - Modification of the Revised Faces Pain Scale, as seen on screen. This prompt was triggered to display on Get- WellNetwork 45 minutes after a medication was withdrawn from automated medication dispensing. (From Faces Pain Scale–Revised [FPS-R]. www.iasp-pain.org/fpsr. Copyright � 2001, International Association for the Study of Pain. Repro- duced with permission [Hicks, von Baeyer, Spafford, van Korlaar, & Goodenough, 2001])

216 Rao-Gupta et al.

about pain and pain management during their daily

rounds with the patients, families and health care

teams. During daily nursing leadership rounds, pa-

tients and caregivers were asked how well pain man- agement needs were being addressed. If pain was not

being addressed as expected by the patient and family,

the leader immediately contacted the appropriate

health care team members. The pain treatment plan

was then modified or corrective actions were taken,

and the patient and family were informed by the nurse

leader of the actions taken.

Pain Treatment Evaluation Pathway. The project team sought to integrate IPC with the automated medi-

cation dispensing system (AMD) and document actions

from both systems into the electronic health record

(EHR). The project team had to make several decisions

to design this workflow (Table 2).

Once the team designed new workflows, pilot

testing confirmed the pathway was triggered on

removal of as-needed analgesics from AMD. The sec- ond round of pilot testing verified that a pain reassess-

ment prompt appeared on the patient’s television

within 45 minutes and the pain reassessment entered

by the patient was documented in the EHR. Within

60 minutes of analgesic administration, the nurse is

to assess the effectiveness of the pain treatment.

Nurses were instructed to compare the reassessments

entered through IPC and compare it with the informa-

tion they gathered through direct patient assessment and communication with parents.

Staff Education and Pathway Implementation. Nursing staff on both pilot units were taught the work-

flow and new functionality of IPC. Principles of adult

learning were incorporated to enhance effective

communication and education. Unit-based nurse edu-

cators and IPC champions spent 10-15 minutes

educating each nurse to ensure that all necessary in- struction was completed and understanding was veri-

fied. On August 26, 2014, once all testing and

education was completed, the Pain Pathway was pi-

loted on the two study units. The Pain Pathway

included (1) new admission assessment questions,

(2) integration between IPC and AMD to trigger the

Pain Pathway; and (3) integration between IPC and

EHR to document patient or parent reported pain reas- sessment and treatment effectiveness (see Fig. 2).

Data Collection and Analysis The primary outcome measure of this performance

improvement initiative was the proportion of

TABLE 2.

Pain Treatment Evaluation Challenges, Decisions and Rationales for Those Decisions

Challenge Decision Rationale

What would trigger the Pain Pathway?

Limit triggering of Pain Pathway to the removal of PRN analgesics from AMD.

� Limit number of times patients on scheduled analgesics would be prompted to reassess pain and evaluate treatment effectiveness.

� The project team did not want to fatigue patients or families with too many on screen prompts.

What should the interval between PRN analgesic removal from AMD and time IPC prompts patient and parent for reassessment and evaluation of treatment effectiveness?

Set interval between PRN analgesic removal and IPC prompt to 45 minutes.

� Nurse reassessment goal was 60 minutes after the administration of an analgesic

� We wanted patient/parent to reassess pain and effectiveness of intervention before the nurse assessment of treatment effectiveness.

What measure should the patient and parents use to reassess pain and evaluate treatment effectiveness?

The Revised Faces Pain Scale (Hicks et al. 2001) with 11 options (0-10), even though the validated scale only includes even numbers corresponding to the 6 faces (see Fig. 4).

� The on-screen prompt provides limited space.

� The hospital uses five different valid and reliable pain scales to meet the varied developmental needs of patients served.

� Pain management champions were concerned that standard pain scales are not validated for parent-proxy reporting of children’s pain.

� There was no way to distinguish self-report from parent report through IPC in EHR.

How to reconcile self-report communicated verbally to the nurse and IPC reassessments documented in EHR?

Reassessments to be documented in EHR by the nurse based on the patient/parents’ feedback

� Both responses were reviewed by the nurse with appropriate intervention taken.

PRN ¼ as needed; AMD ¼ automated medication dispensing system; IPC ¼ interactive patient care; EHR ¼ electronic health record.

217Interactive Patient Care Technology Improve Pain Management

positive responses to the Child Hospital Consumer

Assessment of Healthcare Providers and Systems

(Child HCAHPS) (National Research Corporation,

2014-2016) question ‘‘Did staff do everything they

could to manage your child’s pain?’’ The percentage

is calculated as the proportion of patients who re-

sponded ‘‘always’’ out of all responses to this ques- tion. This HCAHPS question is included on the

patient experience survey mailed to families within

30 days of hospital discharge. However, patients hos-

pitalized on Hematology/Oncology Unit are surveyed

no more frequently than every 3 months. Far fewer

surveys are expected from the Hematology/

Oncology Unit than from the Pediatric Surgical

Unit because of the inherent differences in these

pilot unit patient volumes and the frequent repeti-

tive hospitalizations required by some Hematology/

Oncology Unit patient chemotherapy protocols.

Difference in proportion of positive responses on

the HCAHPS pain management satisfaction question

were evaluated with c2 tests and SPSS Software Version 17.0 (SPSS Inc., Chicago, IL). A minimum of 30 surveys were needed for each pilot unit at each

time point to analyze differences in proportions. Level

of significance was set at p < .05. Admission intake data acquisition was completed

within the first 24 hours of admission. Intake data were

audited on a monthly basis and included in raw data re-

ports requested from the Data Analytics and Reporting

team.

p ri n t &

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218 Rao-Gupta et al.

Patient-generated pain reassessments were docu-

mented in the patient’s record in real time, within

the 45- to 60-minute window when the prompt ap-

peared on the patient’s TV screen (IPC). Nurses

continued to document pain assessments, treatments,

and effectiveness of treatments in the same manner

as before the pilot. The frequency of documentation was included in monthly raw reports from the Data An-

alytics and Reporting team. These data were then

further analyzed by the core project team and the

unit-based teams.

RESULTS

By the end of the first year of implementation, there

had been a steady increase in use of IPC and the Pain

Pathway. Specifically, the new admission assessment

questions were consistently completed by direct care

nurses (Fig. 5). Pain reassessment by patients and fam-

ilies through the Pain Pathway also steadily increased on both pilot units (Fig. 6). In addition, documentation

in the EHR of nonpharmacologic methods used to help

patients manage and cope with pain also increased

(Fig. 7).

Proportion of positive responses from patients

and parents on the Hematology/Oncology Unit signifi-

cantly increased from fiscal year 2014 (FY14) to fiscal

year 2015 (FY15) (p ¼ .036) and from FY14 to fiscal year 2016 (FY16) (p ¼ .028); but there was no differ- ence in the proportion of positive responses from

FY15-FY16 (p ¼ .87) or for each year compared with

FIGURE 5. - Documented responses for new

the CHA benchmark (FY14 p ¼ .255, FY15 p ¼ .32, FY16 p ¼ .26) (see Fig. 1). There was no significant dif- ference in the proportion of positive responses from

patients and families on the Pediatric Surgical Unit

(FY14-FY15 p ¼ .8, FY14-FY16 p ¼ .11, FY15-FY16 p ¼ .44); or for each year compared with the CHA benchmark (FY14 p ¼ .73, FY15 p ¼ .91, FY16 p ¼ .63). Finally, there was no significant difference in the proportion of positive responses from the com-

bined patients and parents of the two pilot units for

each year compared with the CHA benchmark (FY14

p ¼ .52, FY15 p ¼ 1, FY16 p ¼ .49); or from FY14- FY15 (p ¼ .2) and FY15-FY16 (p ¼ .27). However, the positive responses from the combined patients

and parents of the two pilot units significantly increased from FY14-FY16 (p ¼ .006).

DISCUSSION

The Pain Pathway pilot was initiated in response to a perceived disconnect among health care providers,

patients, and parents regarding the strategies and

effectiveness of pain treatment plans. The project

team’s commitment to provide tools to address

pain from admission through discharge helped to

standardize messaging among health care team mem-

bers. The commitment to engage patients and their

parents in conversations about pain also recognized the need to individualize communication about pain

expectations, treatment options, preferences, and

plans.

pain admission assessment questions.

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FIGURE 6. - Percent of patient and family responses to Pain Pathway evaluation of treatment effectiveness television prompts.

p ri n t & w e b 4 C = F P O

219Interactive Patient Care Technology Improve Pain Management

By leveraging IPC, patients and parents were engaged to take an active role in pain treatment plans

and evaluation of treatment outcomes. The increased

amount of documentation related to pain is both the

resultof theproject team’s innovative approachand their

commitment to facilitate conversation about pain. Thus,

FIGURE 7. - Total number of nonpharmacologic interventions FY14 ¼ fiscal year 2014, baseline measure; FY15 ¼ fiscal year 2 patients.

documentation of nonpharmacologic interventions increased even though this was not hard wired into the

workflow designs. This performance improvement proj-

ect, and other unit-based pain management initiatives,

improved active communication about pain and partner-

ship with patients and parents to effectively change the

documented for patients hospitalized on two pilot units. 015; FY16 ¼ fiscal year 2016. # Unique Pts. ¼ no. of unique

220 Rao-Gupta et al.

culture of the two pilot units to be more sensitive to chil-

dren’s pain and patient and parents’ hospital experi-

ences. HCAHPS scores significantly increased as a result.

Poor correlation between pain intensity and

patient-reported satisfaction with pain management

in hospitals is well documented, and explanations for

this dissonance are varied and complex (Golas, Park, & Wilkie, 2016). Recently, Centers for Medicare and

Medicaid Services (CMS) announced plans to remove

the pain management dimension from the scoring for-

mula used in the hospital value-based purchasing pro-

gram (CMS, 2017). However, CMS also announced

the pain management questions will remain on

HCAHPS and will continue to be publicly reported.

Despite the lack of evidence to support the value of this care quality measure, hospital administrators, as

well as nurses involved in pain management, seek to

satisfy patients’ and families’ expectations for pain

management and perceptions of the health care teams’

responsiveness to pain management. Documented

evidence-based interventions that improve patient-

and family-reported satisfaction with pain management

are needed. We reframed our approach to patient and family satisfaction as a patient and family engagement

and communication performance improvement proj-

ect. We have provided evidence that this intervention

increased patient and family satisfaction with pain

management as well as documentation of pain admis-

sion assessments, nonpharmacologic interventions,

and evaluation of treatment effectiveness (reassess-

ment) on our two pilot units. The Pain Pathway was implemented throughout

the hospital on all the inpatient units, except the

neonatal intensive care unit, on April 19, 2016. Expan-

sion of the project has promoted additional strategies

to engage patients, parents, and health care teams in

conversations about pain. For example, child life spe-

cialists now create action plans for patients who

need additional support. These plans include cues and suggestions, such as:

� When I am in pain, I may pinch, scratch or bite; � Counting and singing help me calm down when I am up-

set; or,

� If I am becoming tense, please remind me to squeeze my stress ball.

Child life specialists post action plans on patient

doors to cue health care team members before they

enter the patient’s room. Partnering with child life spe- cialists has been instrumental for increasing pain

awareness and identifying additional techniques to

reduce pain and strategies to promote patients’ and

parents’ abilities to cope during hospitalization.

Limitations There are several limitations to the Pain Pathway work-

flows. The Pain Pathway is triggered by the removal of

an as-needed analgesic from the AMD, and the patient is prompted to reassess pain and evaluate treatment

effectiveness 45 minutes later. There can be a delay

from the time the medication is removed from the

AMD until the medication is given to the patient.

Consequently, the patient may be prompted to reassess

his or her pain and evaluate the effectiveness of the

intervention before the reasonable onset or peak anal-

gesic effect. Once the Pain Pathway has been triggered by the removal of the medication from the AMD, it

cannot be stopped or cancelled. If the patient later re-

fuses the medication, reassessment will still be promp-

ted 45 minutes after the removal of the medication

from the AMD. As-needed analgesics, like acetamino-

phen, are also indicated for fever. Unfortunately, the

medications that trigger the Pain Pathway are identified

by as-needed status and name, not by as-needed indica- tion. There is no way to identify at the time of removal

from AMD, or in the EHR, that the as-needed medica-

tion is being administered by the nurse for other valid

reasons.

Implications for Nursing Practice Based on the outcomes measured and feedback gath-

ered from staff and families over the course of this

initiative, the findings suggest that using multiple mo-

dalities is essential to effectively engage parents/care- givers in their child’s care. A multidisciplinary team

that communicates a consistent message about part-

nership and decision making is integral in shifting the

culture around pain management to be more patient-

centric. Truly listening to the patient and family is para-

mount in creating an effective and individualized plan

of care. Furthermore, finding additional ways to

harness technology and connect unique systems will assist in building a more comprehensive picture of pa-

tient and family preferences, which in turn must

continually be incorporated into care team recommen-

dations to move patient care forward in a meaningful

way.

CONCLUSIONS

This innovative performance improvement project has had a positive impact by engaging patients, families,

and health care team members to partner in managing

pain. Reframing our approach for improving patient

and family satisfaction with pain management by

leveraging IPC to engage patients and families in pain

221Interactive Patient Care Technology Improve Pain Management

care planning was effective. Patient and family satisfac-

tion with pain management improved, and documenta-

tion of pain admission assessments, nonpharmacologic

interventions, and evaluation of treatment effective-

ness (reassessment) improved. Additional testing of

this intervention through replication at other hospitals

is needed to provide further evidence of the effective- ness of this approach.

When the mother of a surgical patient was inter-

viewedregardinghospitalexperiencesand communica-

tion with the health care team about pain management,

she stated:

‘‘Being diagnosed with something that isn’t very

common is scary.. As a parent, you want to comfort, and make him feel better. It’s nice to know that the people here are doing what I can’t do to make him

feel better. To manage his pain, it seems that they are

just as concerned as I am; it’s comforting to know

that they’re watching it really close and doing what

they need to, to help. The doctors and nurses keep

me very involved in the steps that they are going to

take to help manage his pain.so it’s really nice to be kept in the loop with not just his medications, but the other things that they are doing to help him. I’m

really glad we’re here.’’

Acknowledgments

The authors would like to thank the departments of nursing,

clinical and organizational development, information tech-

nology, nursing informatics, and pharmacy for their dedi-

cated effort to this project.

REFERENCES

Medicare Program; hospital inpatient value-based purchas- ing program. Federal Register, 76, FR.26489.

Golas, M., Park, C. G., & Wilkie, D. J. (2016). Patient satisfaction with pain level in patients with cancer. Pain Management Nursing, 17(3), 218–225.

Habich, M., Wilson, D., Thielk, D., Melles, G. L., Crumlett, H. S., Masterton, J., & Mcguire, J. (2012). Evalu- ating the effectiveness of pediatric pain management guide- lines. Journal of Pediatric Nursing, 27(4), 336–345.

Hicks, C. L., von Baeyer, C. L., Spafford, P., von Korlaar, I., & Goodenough, B. (2001). The Faces Pain Scale–Revised: Toward a common metric in pediatric pain measurement. Pain, 93, 173–183.

Kompany, L., Luis, K., Manganaro, J., Motacki, K., Mustacchio, E., & Provenzano, D. (2016). Children’s specialized hospital and GetWellNetwork collaborate to improve patient education and outcomes using an innova- tive approach. Pediatric Nursing, 42(2), 95–99.

Kozlowski, L. J., Kost-Byerly, S., Colantuoni, E., Thompson, C. B., Vasquenza, K. J., Rothman, S. K., Billett, C., White,E.D.,Yaster,M.,&Monitto,C.L.(2014).Painprevalence, intensity, assessment and management in a hospitalized pedi- atric population. Pain Management Nursing, 15(1), 22–35.

McGrath, P. J., Walco, G. A., Turk, D. C., . (2008). Core outcome domains and measures for pediatric acute and

chronic/recurrent pain clinical trials: PedIMMPACT recom- mendations. Journal of Pain, 9(9), 771–783. NRC Health, (2014-2016), Child Hospital Consumer

Assessment of Healthcare Providers and Systems (Child

HCAHPS). Retrieved from www.nrchealth.com. Palermo, T. M., Valrie, C. R., & Karlson, C. W. (2014).

Family and parent influences on pediatric chronic pain. American Psychologist, 69(2), 142–152. Simons, J. (2015). A proposed model of the effective

management of children’s pain. Pain Management Nursing, 16(4), 570–578. Simons, L. E., Goubert, L., Vervoort, T., & Borsook, D. (2016).

Circles of engagement: Childhood pain and parent brain. Neuroscience and Biobehavioral Reviews, 68, 537–546. Solodiuk, J. C., Brighton, H., Michale, J., Lochiatto, J.,

Logan, D. E., Sager, S., Zurakowski, D., & Berde, C. B. (2014). Documented electronic medical record-based pain intensity scores at a tertiary pediatric medical center: A cohort anal- ysis. Journal of Pain and Symptom Management, 48(5), 924–933. Walther-Larsen, S., Pedersen, M. T., Friis, S. M.,

Aagaard, G. B., Rømsing, J., Jeppesen, E. M., & Friedrichsdorf, S. J. (2017). Pain prevalence in hospitalized children: A prospective cross-sectional survey in four Danish university hospitals. Acta Anaesthesiologica Scandinavica, 61(3), 328–337.

Copyright © 2017 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved.Copyright © 2017 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved.

e806 www.ccmjournal.org August 2017 • Volume 45 • Number 8

Address requests for reprints to: Patricia C. Dykes, PhD, RN, Center for Patient Safety, Research and Practice, Brigham and Women’s Hospital, 1620 Tremont St., Boston, MA. E-mail: [email protected]

Objectives: Studies comprehensively assessing interventions to improve team communication and to engage patients and care part- ners in ICUs are lacking. This study examines the effectiveness of a patient-centered care and engagement program in the medical ICU. Design: Prospective intervention study. Setting: Medical ICUs at large tertiary care center. Patients: Two thousand one hundred five patient admissions (1,030 before and 1,075 during the intervention) from July 2013 to May 2014 and July 2014 to May 2015. Interventions: Structured patient-centered care and engagement training program and web-based technology including ICU safety checklist, tools to develop shared care plan, and messaging platform. Patient and care partner access to online portal to view health infor- mation, participate in the care plan, and communicate with providers. Measurements and Main Results: Primary outcome was aggregate adverse event rate. Secondary outcomes included patient and care partner satisfaction, care plan concordance, and resource utilization. We included 2,105 patient admissions, (1,030 baseline and 1,075 during intervention periods). The aggregate rate of adverse events fell 29%, from 59.0 per 1,000 patient days (95% CI, 51.8–67.2) to 41.9 per 1,000 patient days (95% CI, 36.3–48.3; p < 0.001), dur- ing the intervention period. Satisfaction improved markedly from an overall hospital rating of 71.8 (95% CI, 61.1–82.6) to 93.3 (95% CI, 88.2–98.4; p < 0.001) for patients and from 84.3 (95% CI, 81.3– 87.3) to 90.0 (95% CI, 88.1–91.9; p < 0.001) for care partners. No change in care plan concordance or resource utilization.

Copyright © 2017 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved. DOI: 10.1097/CCM.0000000000002449

*See also p. 1424. 1Center for Patient Safety, Research and Practice, Brigham and Women’s Hospital, Boston, MA.

2Harvard Medical School, Boston, MA. Registration: ClinicalTrials.gov, number NCT02258594. Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal’s website (http://journals.lww.com/ccmjournal). Supported, in part, by The Gordon and Betty Moore Foundation. Dr. Dykes’s institution received funding from the Gordon and Betty Moore Foundation (GBMF). Dr. Rozenblum’s institution received funding from the GBMF; he disclosed that he is a cofounder of Hospitech Respira- tion; and he disclosed work for hire. Dr. Dalal’s institution received fund- ing from the GBMF. Dr. Massaro’s institution received funding from the GBMF and from Risk Management Foundation Insurance Company. Dr. Chang received support for article research from the National Institutes of Health. Dr. Clements’ institution received funding from the GBMF. Dr. Collins’ institution received funding from the GBMF, from research grants funded by Agency for Healthcare Research & Quality, and research contracts funded by the Food and Drug Administration and ASPR. Dr. Donze’s institution received funding from the GBMF, and he received funding from Swiss National Science Foundation. Dr. Gazarian’s insti- tution received funding from the GBMF. Dr. Hanna disclosed work for hire. Dr. Lehmann’s institution received funding from the GBMF. Dr. Mor- rison’s institution received funding from the GBMF. Dr. Samal’s institu- tion received funding from the GBMF. Dr. Schnock’s institution received funding from the GBMF, and she received support for article research from the GBMF. Dr. Bates’ institution received funding from the GBMF; he received funding from SEA Medical, Intensix, EarlySense, QPID, Zynx, CDI (Negev), Enelgy, ValeraHealth, and MDClone; and he disclosed that he is a coinventor on Patent No. 6029138 held by Brigham and Women’s Hospital on the use of decision support software for medical manage- ment, licensed to the Medicalis Corporation, where he holds a minority equity position. The remaining authors have disclosed that they do not have any potential conflicts of interest.

Prospective Evaluation of a Multifaceted Intervention to Improve Outcomes in Intensive Care: The Promoting Respect and Ongoing Safety Through Patient Engagement Communication and Technology Study*

Patricia C. Dykes, PhD, RN1,2; Ronen Rozenblum, PhD1,2; Anuj Dalal, MD1,2; Anthony Massaro, MD1,2; Frank Chang, MSE1; Marsha Clements, MSN, RN1; Sarah Collins, PhD, RN1,2; Jacques Donze, MD1; Maureen Fagan, DNP, RN1; Priscilla Gazarian PhD, RN1; John Hanna, BS1; Lisa Lehmann, MD1,2; Kathleen Leone, MBA, RN1; Stuart Lipsitz, ScD1,2; Kelly McNally, BS1; Conny Morrison, BA1; Lipika Samal, MD, MSc1,2; Eli Mlaver, BA1; Kumiko Schnock, PhD1,2; Diana Stade BA1; Deborah Williams, BA1; Catherine Yoon, MPH1; David W. Bates, MD, MSc1,2

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Conclusions: Implementation of a structured team communication and patient engagement program in the ICU was associated with a reduction in adverse events and improved patient and care part- ner satisfaction. (Crit Care Med 2017; 45:e806–e813) Key Words: checklist; medical errors; medical informatics; patient- centered care; patient engagement

ICU hospitalizations can be frightening and may have long-term consequences for patients including posttraumatic stress disorder (1). Furthermore, patients cared for in ICUs are particularly vulnerable to adverse events (AEs) (2). Although checklists have been found to be effective in reduc- ing specific types of AEs in critical care, preventable AEs still frequently occur (2). Recent literature suggests that the ICU experience could be safer if care were more patient-centered and if patients could be engaged more effectively (3).

Active partnerships among health professionals, patients, and families can improve the quality, safety, and delivery of healthcare (4). Evidence indicates that patient engagement affects self-management, treatment adherence, satisfaction, and healthcare costs (5). However, intensive care is a diffi- cult environment in which to engage patients—because most patients are critically ill and many are incapacitated (6). Yet, patients and families want to be actively involved, and many patients have a “care partner.” Care partners can be a family member or friend who works with the patient to engage with the healthcare team even when the patient is not physically able. A care partner helps with care navigation including com- munication with providers, asking for clarity around complex issues, letting the team know about patient preferences, and facilitating follow-up on unresolved issues (7).

Operationally, patient engagement in the ICU may include participation in rounds, communication about values and goals, and protection of individual respect and dignity (4). Interprofessional communication related to the patient’s goals and care plan occurs during patient rounds. Previous studies focusing on provider members of the care team indicate that a standardized interprofessional rounding structure facilitated by electronic health record (EHR) data and checklist tools is associated with improved adherence with the standard of care, patient outcomes, and provider satisfaction (8, 9). Earlier work at our institution highlights the importance of engaging with patients and care partners to identify goals of care and to jointly assess the effectiveness of treatment in meeting goals and restoring life (10). However, the use of health information technology (IT) to support integrated patient-centered model of team communication in the ICU, characterized by shared checklists, health information, and goals across team members has not been reported. Patient portals are another way to pro- mote engagement and enhance patient-provider partnerships (11). The type of information included in patient portals varies markedly by site (12). Portal content can range from EHR data (laboratory results, medications, problems) to patient educa- tion and self-management tools. With patient permission,

care partners can access their portal. Outpatient portals have been shown to improve patient-provider communication and patient satisfaction (13). However, the use of portals in hospi- tals, especially in the ICU, has been limited (14).

Despite evidence that health IT and patient-centered care can improve safety and outcomes, little research has assessed interventions that leverage health IT to improve team com- munication while engaging patients and care partners in the ICU. Therefore, we designed an intervention and conducted a prospective study to assess the effect of a patient-centered care and engagement program enabled by health IT on care delivered in the ICU.

METHODS This prospective pre-post study was conducted in two medical ICUs (MICUs) at a large tertiary care center from July 1, 2013, through June 8, 2014 (baseline period), and from July 1, 2014, through May 29, 2015 (intervention period). Implementation of the intervention, including training, was completed by June 30, 2014. The institutional review board approved the study protocol.

Study Unit Descriptions and Patient Eligibility Both MICUs operate using a “closed” model, whereby the criti- cal care team maintained responsibility for all patients on the unit (15). The ICU staff (physicians and nurses) rotated on both units. Each unit had a physician team comprised of an attending physician, critical care fellows, interns, and residents. There was 24-hour attending-level coverage for each unit, and physician and nursing staff worked 12-hour shifts. Residents rotated in 2-week blocks. Physician and nurse staffing ratios and work schedules were the same during the 11 months of baseline and intervention data collection periods. Any patient 18 years old or older and admitted to the ICU for 24 hours or longer was eligible to participate.

Preintervention Period Attending physicians, fellows, residents, and nurses participated in daily rounds and used existing paper (safety checklist, nursing flow sheet, care plan) and electronic tools (computerized pro- vider order entry, laboratory/test results, medication adminis- tration record). There was no preexisting standardized approach for team communication or patient engagement. During rounds, the team verbally reviewed a paper-based safety checklist that included prompts for standard safety elements (16).

Intervention The Promoting Respect and Ongoing Safety through Patient Engagement Communication and Technology (PROSPECT) intervention was a systems-based patient-centered care and engagement program that was introduced to providers (physi- cians and nurses) to enhance their responsiveness to patients and care partners (Fig. 1; Appendix A, Supplemental Digital Content 1, http://links.lww.com/CCM/C605). The intervention consisted of the following components: 1) a 60-minute train- ing session that introduced the Patient SatisfActive Model that included structured patient-centered care training to enhance

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responsiveness to the needs, concerns, and expectations of patients and care partners and interactive training on the use of a web-based toolkit to facilitate team communication and patient engagement (Appendixes B1, Supplemental Digital Content 2, http://links.lww.com/CCM/C606; Appendix B2, Supplemental Digital Content 3, http://links.lww.com/CCM/ C607). 2) A web-based toolkit including a) an ICU safety check- list prepopulated with real-time EHR data, b) shared patient and provider care planning tools, and c) a messaging platform for communicating with providers and patients. The web- based toolkit was used by providers for all patients during the intervention period. In addition, all patients and care partners received the Patient SatisfActive Model in which nurses asked patients at admission, during each shift, and at time of ICU dis- charge about their perceived needs, concerns, and expectations. Patient wishes were routinely discussed by the team during interprofessional rounds and were integrated into the daily care plan as needed. Patients capable of providing informed consent (or proxy) were eligible to use the patient portal accessible on hospital-issued iPads (iPad Air; Apple, Cupertino, CA) available at every patient’s bedside to view personal health information, to participate in developing the care plan, and to communicate with providers. Research assistants approached eligible patients (or proxy) to participate in using the portal. The informed con- sent process was extensive (i.e., a 10-page informed consent and access authorization form). Once enrolled, patients/proxies were shown how to use the portal and could access the portal throughout their stay in the MICU.

Main Outcome Measures The primary outcome was the aggregate rate per 1,000 patient days of selected AEs, defined as failed processes of care and/ or unintended consequences of medical care that can lead to

patient harm (2, 17). To avoid outcomes ascertainment bias, we included only those AEs that are routinely reported within established organizational surveillance processes (and there- fore captured and vetted independently of the study team): falls, pressure ulcers, catheter-associated urinary tract infec- tions, central catheter-associated bloodstream infections, and ventilator-associated events. Secondary outcomes were patient and care partner satisfaction, care plan concordance (e.g., agreement on the care plan) between the patient and providers, and healthcare utilization. Secondary outcome data were col- lected in REDCap (18) using organizational reporting systems. Validated survey instruments were administered with verbal consent to a randomly selected subsample of patients (19) care partners (20), and providers to assess care plan concordance (21, 22). Patient satisfaction data were collected through tele- phone using the Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) (23) survey 6 weeks after discharge. Hospitalized patients (or a care partner) as well as their bedside nurse and a physician were interviewed at least 48 hours into admission using a validated care plan concor- dance assessment tool (22) modified to include the patient’s key recovery goal (24). Outcome measure definitions, surveys, and data sources are included in Table 1. Process measures included the number of patients/care partners who provided informed consent to use the patient portal.

Statistical Analysis Based on previously reported AE rates (2) and the effect of com- munication interventions (8) in critical care, we hypothesized that there would be a 28% decrease in the rate of AEs in the base- line period to the intervention group. We estimated that a total sample size of 1,800 would provide a statistical power of 80% to detect this decrease, at a two-sided significance level of 5% using a propensity-adjusted two sample Poisson test (30).

Demographic characteristics for patient admissions are described using proportions for dichotomous variables and means for continuous variables. Demographics are compared before and during the intervention using Pearson’s chi-square test for dichotomous variables and Wilcoxon rank-sum tests for continuous variables. We used weighted propensity score methods to account for differences in observed participant characteristics between the baseline and intervention peri- ods. For the patient/care partner surveys, the following demographics are adjusted: gender, age, education, race, self- reported health status (patient), and relationship to patient (care partner). Using the weighted propensity score method, each patient was weighted by the inverse propensity of being in the baseline or intervention period in all analyses. The pro- pensity was estimated using logistic regression with potential confounders as covariates. Weighted propensity score methods control for confounding factors better than regression models alone (31). The robust SEs used with the weighted propensity score approach also accounted for repeated measures (stays) on the same patient (patients who had multiple stays during the study). AE rates were compared using Poisson regres- sion, with a dichotomous covariate for before versus after the

Figure 1. The PROSPECT (Promoting Respect and Ongoing Safety through Patient Engagement Communication and Technology) intervention included 1) a nontechnical structured patient-centered care and engagement model (Patient SatisfActive Model) and 2) a web-based technology to facilitate communication and to engage patients/care partners with providers in their care plan. Providers (physicians, nurses) received structured patient-centered care and engagement training using the Patient SatisfActive Model and a web-based patient-centered toolkit comprised of an ICU safety checklist, shared patient and provider care planning and messaging platform. Providers accessed the toolkit via mobile and desktop devices. Patients/care partners were given access to a portal via iPads (Apple, Cupertino, CA) to view health information, participate in the care plan, and communicate with providers. Detailed information about the PROSPECT intervention components is included in Appendix A (Supplemental Digital Content 1, http://links.lww. com/CCM/C605).

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intervention period. Patient and care partner experience were compared using robust linear regression for ordinal outcomes. Mean global care plan concordance scores were compared in the baseline and intervention periods using generalized esti- mating equations to account for multiple ratings on the same patient (32). Healthcare utilization was compared before ver- sus intervention periods using exponential regression.

For the main outcome of the rate of AEs, we also performed an interrupted time series (33) (segmented Poisson regression) analysis to determine whether the changes in rates pre versus post were due to changes in the trends pre versus post, and not the same downward secular trend that continued from pre to post. As a sensitivity analysis, weighted estimating equations were used to account for missing data (34). All analyses were performed using SAS version 9.4 (SAS Institute, Cary, NC).

Role of the Funding source This project was supported by a Grant from the Gordon and Betty Moore Foundation (GBMF). The GBMF did not partici- pate in the design of the study, the analysis or the interpreta- tion of the data, the writing of this article, or the process to submit this article for publication.

RESULTS

Patient Admissions A total of 2,105 patient admissions (n = 1,030 during baseline, n = 1,075 during intervention) were reviewed for AEs. Demo- graphics were similar during baseline and intervention, but patients admitted in the intervention period were less likely to be white and more often had Medicaid insurance (Table 2).

TABLE 1. Promoting Respect and Ongoing Safety Through Patient Engagement Communication and Technology Outcome Measures, Timing, Data Sources, and Methods

Measure Timing Data Source Method/Tool

Aggregate adverse events. Failed processes of care and/or unintended consequences of medical care that can lead to patient harm. Includes:

1) Blood stream infections (25) 2) Ventilator-associated event (26) 3) Catheter-associated urinary tract

infections (27) 4) Falls (28) 5) Pressure ulcers (28)

Ongoing (independent of Promoting Respect and Ongoing Safety through Patient Engagement Communication and Technology Project)

BWH Quality and Infection Control Departments

Used standard definitions (25–28) for measures that involved data routinely collected by the BWH Quality and Infection Control Departments (external to study team) and events submitted by clinicians

Care partner (family) reported experience and satisfaction

Prior to transfer from ICU In-person survey with care partner/family by research staff

FS-ICU (20) composite score based on average of all 24 items (FS- ICU total, satisfaction with care, and satisfaction with decision- making) FS-ICU includes a 5-point Likert scale 1 (excellent) to 5 (poor). All items give response option “not applicable.”

1) A random sample of care partners 2) Sample size based on power

calculation

Patient reported experience and satisfaction

45 d after discharge from hospital

Telephone Survey of Patients by research staff

Hospital Consumer Assessment of Healthcare Providers and Systems survey (29) “Top Box Score” e.g., Patients who gave their hospital a rating of 9 or 10 on a scale from 0 (lowest) to 10 (highest)

1) Random sample of care partners 2) Sample size based on power

calculation

Care plan concordance: The degree of agreement of patient’s overall goal for hospitalization between patient/ care partner, responding physician, and nurse.

At time of transfer (ICU) Patients, care partner/family, physician, nurse interviews

Interview based survey based on Haberle (24)

1) Random sample of care partners 2) Sample size based on power

calculation

Healthcare utilization (proxy) Post discharge BWH administrative data

Administrative report 1) Length of stay 2) 30-d readmission

BWH = Brigham and Women’s Hospital, FS-ICU = Family Satisfaction-ICU.

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Patient portal enrollment was 18% of all patient admissions during the intervention period and was higher among patients who were white, younger, and those with private insurance.

Provider Participants All 219 physicians and 92 nurses working in the MICU dur- ing the intervention period were trained and participated in the PROSPECT intervention. The majority of provider partici- pants (91% physicians and 79.3% nurses) worked in the MICU during the baseline period.

Outcomes There was a 29% relative reduction in the aggregate rate of AEs, from 59.0 per 1,000 patient days (95% CI, 51.8–67.2) to 41.9 per 1,000 patient days (95% CI, 36.3–48.3), p value of less than 0.001 (Table 3) and pre-post, p value equals to 0.049 for the interrupted time series. This translates into a reduction of 17.1 AEs per 1,000 patient days. Also, results were very similar using weighted estimating equations to account for missing data.

The percent of patients who reported a top box score (9 or 10 on the 0–10 HCAHPS question [19]) for their overall hospital rating significantly improved from 71.8 (95% CI, 61.1–82.6) to 93.3 (95% CI, 88.2–98.4), p value of less than 0.001. Care partner satisfaction with the ICU experience also improved significantly from 84.3 (95% CI, 81.3–87.3) to 90.0 (95% CI, 88.1–91.9), p value of less than 0.001. Care team

concordance with patient’s care plan and resource utilization was unchanged.

DISCUSSION We implemented a multifaceted intervention in the ICU and observed improved outcomes with about a one-third lower rate of AEs, as well as large improvements in satisfaction scores for MICU patients and their care partners. These improvements are important, as the ICU is an inherently risky place where both patients and care partners can feel alienated. As with any com- plex intervention, we cannot determine which component had the greatest impact, but we believe the improvements are related to multiple factors. We attribute the marked improvement in AEs and satisfaction to use of the safety checklist tool and our efforts at engaging patients, care partners, and care team mem- bers via the various intervention components. The intervention was directly integrated into multidisciplinary rounds with the intent of improving communication among patients and pro- viders. Daily use of the web-based safety checklist enabled review of the critical care safety elements; patient goals, preferences, and priorities were systematically addressed. This review trans- lated into routinely focusing on patients’ concerns, updating the care plan, and reviewing adherence (or rationale for nonadher- ence) with standard critical care safety elements (Appendix A, Supplemental Digital Content 1, http://links.lww.com/CCM/ C605) such as catheter days and mobility status (3). All frontline

TABLE 2. Baseline Characteristics of Patients at the Time of the Enrollment Characteristic Baseline Intervention p Portal Users Nonusers p

No. of unique admissions 1,030 1,075 194 881 0.03

White 730 (70.87%) 717 (66.70%) 0.04 146 (75.26%) 571 (64.81%)

Black 145 (14.08) 152 (14.14) 19 (9.79) 133 (15.10)

Hispanic 74 (7.18) 91 (8.47) 11 (5.67) 80 (9.08)

Other 17 (1.65) 37 (3.44) 3 (1.55) 34(3.86)

Unknown 64 (6.21) 78 (7.26) 15 (7.73) 63 (7.15)

Medicaid 75 (7.30) 129 (12.01) 0.003 17 (8.76) 112 (12.73) 0.06

Medicare 508 (49.46) 497 (46.28) 82 (42.27) 415 (47.16)

Private 408 (39.73) 398 (37.06) 89 (45.88) 309 (35.11)

Self pay 14 (1.36) 22 (2.05) 3(1.55) 19 (2.16)

Other 22 (2.14) 28 (2.61) 3(1.55) 25 (2.84)

Missing 3 1 0 1

Female 505 (49.03) 535(49.77) 0.73 104 (53.61) 431 (48.92) 0.24

Mean age (SD) 60.27 (17.22) 59.92 (17.05) 0.47 58.13 (16.27) 60.31 (17.21) 0.09

Mean Charlson score (SD)a 3.86 (2.67) 4.03 (2.66) 0.08 4.11 (2.69) 4.02 (2.66) 0.67

Mean of median income based on zip code (SD)

69,850.52 (24,784.07)

68,484.54 (25,377.82)

0.10 71,076.23 (23,390.38)

67,919.30 (25,769.10)

0.07

Average total hospital length of stay per patient admission

12.90 (13.96) 13.32 (15.01) 0.99 18.60 (18.07) 12.16 (14.00) < 0.0001

a Higher Charlson score indicates greater risk of 10-yr mortality.

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clinicians actively engaged patients and care partners in address- ing their needs, concerns, and expectations regarding the care plan throughout their MICU stay. This enhanced patient and care partner engagement activity occurred regardless of a use of the patient portal. Although the portal enrollment rate was modest, the tools and workflows offered patients a method of communicating a primary goal for hospitalization, submitting questions regarding the care plan, and viewing their medical problems and goals of care. The aim of these interventions was to shift the clinical paradigm from providers alone determin- ing “What is the matter?” to discovering “What matters to you?” (35), as well as to working collaboratively with patients. Because MICU patients may be too ill to actively participate, a partner- ship between the critical care team and care partners is often needed to provide patient-centered care in the ICU setting (4).

Under value-based purchasing, hospital payments are now tied to quality metrics including AEs and patient experience (36). For that reason, the improvements we found in patient outcomes are important. Other studies have demonstrated improvements in satisfaction, clinical outcomes, and business metrics associated with patient-centered care in acute care settings but not previously in the ICU (37–39). Despite con- certed efforts geared toward improvement, these outcomes are often mixed (40). The improvement in AE rate was driven by catheter-associated urinary tract infections and pressure ulcers. Both of these AEs are fairly frequent and they had relatively high rates in the preintervention period (41, 42), making it easier to demonstrate improvement. Although the other outcomes (with the exception of patient falls) trended in the right direction, the changes were not significant.

TABLE 3. Primary Outcome: Aggregate Adverse Events Comprised of Catheter-Associated Urinary Tract Infection, Bloodstream Infection, Ventilator-Associated Events, Falls, and Pressure Ulcers

Main Outcome: Medical Adverse Events

Total No. of Adverse Events (Rate per 1,000 Patient Days) (95% CI)

Medical Adverse Event Type Before (n = 997 Admissions) After (n = 1,050 Admissions) p

All adverse events 59.0 (51.8–67.2) 41.9 (36.3–48.3) < 0.001

Catheter-associated urinary tract infection 3.9 (2.5–5.9) 1.1 (0.5–2.4) 0.005

Bloodstream infection 1.6 (0.8–3.2) 0.9 (0.4-2.2) 0.36

Ventilator-associated events 10.1 (7.9–13.1) 9.5 (7.2–12.6) 0.75

Falls 0.5 (0.2–1.6) 0.5 (0.2–1.6) 0.93

Pressure ulcers 42.9 (36.4–50.6) 29.9 (24.9–35.8) 0.003

Weighted propensity-adjusted results, adjusted for gender, age, race, insurance, Charlson comorbidity index, and median income based of patient’s zip code.

TABLE 4. Secondary Outcomes Comprised of Patient Experience, Care Partner Experience, Global Concordance With Patient's Overall Care Plan, and Resource Utilization

Secondary Outcomes Before After p

Patient experience

Overall hospital rating Hospital Consumer Assessment of Healthcare Providers and Systems Top Box Score, range 0–100

71.8% (n = 53; 61.1–82.5) 93.3% (n = 58; 88.2–98.4) < 0.001

Care partner experience

Overall Satisfaction Family Satisfaction-ICU (20) Total Score, range 0–100

84.3% (n = 106; 81.3–87.3) 90.0% (n = 156; 88.1–91.9) < 0.001

Global concordance with patient’s overall care plan

Mean Global Concordance Score (95% CI) 59% (n = 169; 55.3–62.7) 59.1% (n = 93; 54.5–63.8) 0.96

Resource utilization

Mean (median) length of stay (d) medical ICU [range]

4.9 (2) [1–108], n = 881 5.0 (2) [1–115], n = 904 0.61

30-d hospital readmission (95% CI) 0.188 (n = 924; 0.16–0.21) 0.184 (n = 960; 0.16–0.21) 0.82

Weighted propensity-adjusted results, adjusted for gender, age, education, race, self-reported health status (patient), and relationship to patient (care partner).

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Bloodstream infections, ventilator associates events, and falls at baseline were at or below benchmark in the preinterven- tion period (41, 42). Given that these are rare events, there may have been insufficient time in the trial to demonstrate statistical significance.

We found that improving care plan concordance in critical care was challenging. Others have noted that the interventions used to simultaneously treat and diagnose critically ill patients often change rapidly to maintain clinical stability (43). Because the patient portal was specifically configured to facilitate patient- provider messaging and improve patient-provider concordance for key elements of the care plan, the lack of improvement we observed may be explained by the limited use of this component.

Study Limitations This study has a number of limitations. First, it was conducted in two MICUs within a single tertiary care center. Although the results may not be generalizable to other institutions, the fact that the technology is based on standard critical care checklists and was used within typical ICU workflows, it may be generalizable to other ICUs that have adopted these best practices and that have a governance structure in place that allows for engaging staff in quality improvement efforts (8, 9). Second, as a prospective pre-post study, the presence of other factors to minimize AE could have affected our results. How- ever, a post hoc interrupted time series analysis to control for temporal factors indicated significant decreases in AEs dur- ing the intervention period. Third, because our intervention was not blinded, providers who implemented it were aware of the study and the outcome measures. To reduce this potential source of bias, we did not collect or validate any of the AE data but instead used the hospital’s standard AE reporting system. There were key ICU outcomes, such as death and readmission after transfer out of the ICU, that we elected not to include in the aggregate AE measure. Fourth, because a portion of our patient record was paper-based, we were unable to automati- cally calculate Acute Physiology and Chronic Health Evalu- ation scores (44). We did calculate Charlson (45). Charlson does not substitute for an illness severity measure, but it is a marker of long-term outcomes after hospital discharge. Fifth, patients were exposed to the intervention and increased cli- nician attention associated with use of the intervention. It is unclear whether it was the multiple part intervention or the increased clinician attention that contributed most to out- comes. Finally, the limited enrollment of patient portal users and the fact that we were unable to track whether patients allowed additional care partners (or enrolled care partners allowed patients) to access the portal under their login pre- vented us from more robustly evaluating the impact of this technology on patient (or care partner) activation. Further, as noted in Table 4, patient portal users had longer lengths of stay. We attribute this to the fact that patients who had more complicated health issues were in the ICU longer. An unplanned corollary was that longer lengths of stay provided more opportunity for staff to enroll patients or care partners and provided them more opportunity to use the portal.

Clinical Implications To our knowledge, this study is the largest to date to evaluate a patient-centered care model including provider and patient use of web-based technology within a hospital setting (14) and likely the only one targeting portal use in MICU patients and care partners. Providers did routinely use the Patient SatisfAc- tive Model, the electronic checklist, and care planning tools. Patient engagement and satisfaction improved significantly, despite low enrollment in use of the patient portal. Barriers to portal use (46) included the physical status of patients, emo- tional status of care partners, relatively brief lengths of stay, and the onerous tasks associated with subject enrollment. Streamlining enrollment procedures and providing portal access to care partners outside of the hospital could engage geographically distant, but willing care partners. One mean- ingful use provision that has generated debate is requiring a specific proportion of patients to use a portal (47). Activat- ing patients to use portals is complex; the true impact of this technology will only be realized after barriers are overcome. Additional work is needed to identify methods and tools to establish shared accountability and to negotiate responsibility with patients and care partners.

CONCLUSIONS In this study, the use of structured patient-centered care train- ing and web-based technology to engage patients and care partners was associated with decreased rates of selected AEs and improved satisfaction. Further study is needed to deter- mine whether a similar program evaluated over a longer period and in other critical care settings would be as effective.

ACKNOWLEDGMENTS We thank Erin Hartman for editing of the article. We thank Martha Carnie and Karen Spikes and the members of the Brigham and Women’s Hospital Patient and Family Advi- sory Committee members who generously provided input to the Promoting Respect and Ongoing Safety through Patient Engagement Communication and Technology intervention and its evaluation.

REFERENCES 1. Patel MB, Jackson JC, Morandi A, et al: Incidence and risk factors for

intensive care unit-related post-traumatic stress disorder in veterans and civilians. Am J Respir Crit Care Med 2016; 193:1373–1381

2. Rothschild JM, Landrigan CP, Cronin JW, et al: The Critical Care Safety Study: The incidence and nature of adverse events and seri- ous medical errors in intensive care. Crit Care Med 2005; 33:1694– 1700

3. Davidson JE, Powers K, Hedayat KM, et al: Clinical practice guide- lines for support of the family in the patient-centered intensive care unit: American College of Critical Care Medicine Task Force 2004– 2005. Crit Care Med 2007; 35:605–622

4. Brown SM, Rozenblum R, Aboumatar H, et al: Defining patient and family engagement in the intensive care unit. Am J Respir Crit Care Med 2015; 191:358–360

5. Hibbard JH, Greene J: What the evidence shows about patient acti- vation: Better health outcomes and care experiences; fewer data on costs. Health Aff (Millwood) 2013; 32:207–214

Copyright © 2017 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved.

Online Clinical Investigations

Critical Care Medicine www.ccmjournal.org e813

6. Santiago C, Lazar L, Jiang D, et al: A survey of the attitudes and per- ceptions of multidisciplinary team members towards family presence at bedside rounds in the intensive care unit. Intensive Crit Care Nurs 2014; 30:13–21

7. Sarkar U, Bates DW: Care partners and online patient portals. JAMA 2014; 311:357–358

8. Berenholtz SM, Pronovost PJ, Lipsett PA, et al: Eliminating catheter- related bloodstream infections in the intensive care unit. Crit Care Med 2004; 32:2014–2020

9. Conroy KM, Elliott D, Burrell AR: Testing the implementation of an electronic process-of-care checklist for use during morning medical rounds in a tertiary intensive care unit: A prospective before-after study. Ann Intensive Care 2015; 5:60

10. Lilly CM, De Meo DL, Sonna LA, et al: An intensive communication intervention for the critically ill. Am J Med 2000; 109:469–475

11. Nazi KM, Turvey CL, Klein DM, et al: VA OpenNotes: Exploring the experiences of early patient adopters with access to clinical notes. J Am Med Inform Assoc 2015; 22:380–389

12. Collins SA, Rozenblum R, Leung WY, et al: Acute care patient por- tals: A qualitative study of stakeholder perspectives on current prac- tices. JAMIA 2016; 24:e9–e17

13. Krause FS, Walter B, Ott OJ, et al: 15-year survival rates after trans- urethral resection and radiochemotherapy or radiation in bladder can- cer treatment. Anticancer Res 2011; 31:985–990

14. Prey JE, Woollen J, Wilcox L, et al: Patient engagement in the inpa- tient setting: A systematic review. J Am Med Inform Assoc 2014; 21:742–750

15. Rothschild JM: Closed intensive care units and other models of care for critically ill patients. In: Making Health Care Safer: A Critical Analysis of Patient Safety Practices. Shojania K, Duncan B, McDonald K (Eds). Rockville, MD, Agency for Healthcare Research and Quality, 2001

16. Berenholtz SM, Milanovich S, Faircloth A, et al: Improving care for the ventilated patient. Jt Comm J Qual Saf 2004; 30:195–204

17. Bates DW, Cullen DJ, Laird N, et al: Incidence of adverse drug events and potential adverse drug events. Implications for prevention. ADE Prevention Study Group. JAMA 1995; 274:29–34

18. Joynt KE, Harris Y, Orav EJ, et al: Quality of care and patient out- comes in critical access rural hospitals. JAMA 2011; 306:45–52

19. Keith JL, Doucette JN, Zimbro K, et al: Making an impact: Can a train- ing program for leaders improve HCAHPS scores? Nurs Manage 2015; 46:20–27; quiz 27–28

20. Wall RJ, Engelberg RA, Downey L, et al: Refinement, scoring, and vali- dation of the Family Satisfaction in the Intensive Care Unit (FS-ICU) survey. Crit Care Med 2007; 35:271–279

21. O’Leary KJ, Thompson JA, Landler MP, et al: Patterns of nurse-phy- sician communication and agreement on the plan of care. Qual Saf Health Care 2010; 19:195–199

22. O’Leary KJ, Wayne DB, Landler MP, et al: Impact of localizing physi- cians to hospital units on nurse-physician communication and agree- ment on the plan of care. J Gen Intern Med 2009; 24:1223–1227

23. Hospital Consumer Assessment of Healthcare Providers and Sys- tems (HCAHPS): HCAHPS. Available at: http://www.hcahpsonline. org/home.aspx. Accessed April 21, 2017

24. Haberle TH, Shinkunas LA, Erekson ZD, et al: Goals of care among hospitalized patients: A validation study. Am J Hosp Palliat Care 2011; 28:335–341

25. Centers for Disease Control and Prevention. Bloodstream Infection Event (Central Line-Associated Bloodstream Infection and Non-Central Line- Associated Bloodstream Infection). Available at: http://www.cdc.gov/ nhsn/pdfs/pscmanual/4psc_clabscurrent.pdf. Accessed April 21, 2017

26. Centers for Disease Control and Prevention. Ventilator-Associ- ated Event (VAE). Available at: http://www.cdc.gov/nhsn/pdfs/ pscmanual/10-vae_final.pdf. Accessed April 21, 2017

27. Centers for Disease Control and Prevention. Catheter-Associated Urinary Tract Infections (CAUTI). Available at: https://www.cdc.gov/ HAI/ca_uti/uti.html. Accessed April 21, 2017

28. Change to: Montalvo, I.: (September 30, 2007) "The National Database of Nursing Quality IndicatorsTM (NDNQI®)" OJIN: The Online Journal of Issues in Nursing. Vol. 12 No. 3, Manuscript 2. Available at: http://www.nursingworld.org/MainMenuCatego- ries/ANAMarketplace/ANAPeriodicals/OJIN/TableofContents/ Volume122007/No3Sept07/NursingQualityIndicators.html. Accessed April 21, 2017

29. Giordano LA, Elliott MN, Goldstein E, et al: Development, implemen- tation, and public reporting of the HCAHPS survey. Med Care Res Rev 2010; 67:27–37

30. Krishnamoorthy K, Thomson J: A more powerful test for comparing two Poisson means. J Stat Plan Inference 2004; 119:23–35

31. Lunceford JK, Davidian M: Stratification and weighting via the pro- pensity score in estimation of causal treatment effects: A comparative study. Stat Med 2004; 23:2937–2960

32. Ware JH, Lipsitz S, Speizer FE: Issues in the analysis of repeated categorical outcomes. Stat Med 1988; 7:95–107

33. Penfold RB, Zhang F: Use of interrupted time series analysis in evaluating health care quality improvements. Acad Pediatr 2013; 13:S38–S44

34. Henry AJ, Hevelone ND, Lipsitz S et al: Comparative methods for han- dling missing data in large databases. J Vasc Surg 2013; 58:1353– 1359.e6

35. Laurence J, Henderson S, Howitt P: Patient engagement: Four case studies haft highlight the potential for improved health outcomes and related costs. Health Aff 2015; 33:1627–1634

36. The Centers for Medicare and Medicaid Services (CMS): Strength- ening Medicare: Better Health, Better Care, Lower Costs: Efforts Will Save Nearly $120 Billion for Medicare Over Five Years. Avail- able at: http://www.cms.gov/apps/files/medicare-savings-report.pdf. Accessed April 21, 2017

37. Charmel PA, Frampton SB: Building the business case for patient- centered care. Healthc Financ Manage 2008; 62:80–85

38. Isaac T, Zaslavsky AM, Cleary PD, et al: The relationship between patients’ perception of care and measures of hospital quality and safety. Health Serv Res 2010; 45:1024–1040

39. Manary MP, Boulding W, Staelin R, et al: The patient experience and health outcomes. N Engl J Med 2013; 368:201–203

40. Jha AK, Orav EJ, Zheng J, et al: Patients’ perception of hospital care in the United States. N Engl J Med 2008; 359:1921–1931

41. Dudeck MA, Weiner LM, Allen-Bridson K, et al: National Healthcare Safety Network (NHSN) report, data summary for 2012, Device- associated module. Am J Infect Control 2013; 41:1148–1166

42. Massachusetts Health & Hospital Association (MHA): Patient Care Link Quality and Safety Information Website: Available at: http:// patientcarelink.org/. Accessed April 21, 2017

43. Collins SA, Bakken S, Vawdrey DK, et al: Model development for EHR interdisciplinary information exchange of ICU common goals. Int J Med Inform 2011; 80:e141–e149

44. Schneider AG, Lipcsey M, Bailey M, et al: Simple translational equa- tions to compare illness severity scores in intensive care trials. J Crit Care 2013; 28:885 e881–e888

45. Needham DM, Scales DC, Laupacis A, et al: A systematic review of the Charlson comorbidity index using Canadian administrative data- bases: A perspective on risk adjustment in critical care research. J Crit Care 2005; 20:12–19

46. Dalal AK, Dykes PC, Collins S, et al: A web-based, patient-cen- tered toolkit to engage patients and caregivers in the acute care setting: A preliminary evaluation. J Am Med Inform Assoc 2016; 23:80–87

47. CMS: Medicare and Medicaid Programs; Electronic Health Record Incentive Program—Stage 3: 2015 Edition Health Information Technology (Health IT) Certification Criteria, 2015 Edition Base Electronic Health Record (EHR) Definition, and ONC Health IT Certification Program Modifications; Proposed Rules. Washington, D.C., Federal Register, 2015, p. 80