Reducing Hospital Toxicity: Impact on Patient Outcomes

Accepted Manuscript

Reducing Hospital Toxicity: Impact on Patient Outcomes Richard V. Milani , Robert M. Bober , Carl J. Lavie , Jonathan K. Wilt , Alexander R. Milani , Christopher J. White PII: DOI: Reference:

S0002-9343(18)30390-5 10.1016/j.amjmed.2018.04.013 AJM 14641

To appear in:

The American Journal of Medicine

Please cite this article as: Richard V. Milani , Robert M. Bober , Carl J. Lavie , Jonathan K. Wilt , Alexander R. Milani , Christopher J. White , Reducing Hospital Toxicity: Impact on Patient Outcomes , The American Journal of Medicine (2018), doi: 10.1016/j.amjmed.2018.04.013

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Clinical significance 

Circadian rhythms control many physiologic and behavioral functions



Routine hospital care commonly is disruptive to a patient’s intrinsic circadian rhythm which is further compounded by loss of personal control of health information Modest changes in hospital routines can be implemented that reduce circadian

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

disruption and enhance free flow of information to patients 

These changes result in measurable improvements in hospital length of stay,

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readmission, and subjective measures of satisfaction

ACCEPTED MANUSCRIPT Reducing Hospital Toxicity

Reducing Hospital Toxicity: Impact on Patient Outcomes Richard V. Milani, MD†∂, Robert M. Bober, MD†∂, Carl J. Lavie, MD∂, Jonathan K. Wilt†, Alexander R. Milani†∆, Christopher J. White, MD∂

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†Center for Healthcare Innovation, Ochsner Health System, the Department of

Cardiovascular Diseases, John Ochsner Heart and Vascular Institute, Ochsner Clinical School – University of Queensland School of Medicine, New Orleans, Louisiana, and Emory University School of Medicine

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∆

Running Title: Reducing Hospital Toxicity Word Count: 2,530

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Key Words: hospital toxicity, circadian rhythm Disclosures: none

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Presented in part as an abstract at the American Heart Association Annual Scientific

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Sessions, November 2017

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Correspondence to:

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Richard V. Milani, M.D. Center for Healthcare Innovation Ochsner Health System 1514 Jefferson Highway New Orleans, LA. 70121 Tel: (504) 842-5874 Fax: (504) 842-5875 Email: [email protected] All authors had access to the data and a role in writing the manuscript.

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Abstract

Background: Circadian rhythms are endogenous 24-hour oscillations in biologic

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processes that drive nearly all physiologic and behavioral functions. Disruption in circadian rhythms can adversely impact short and long-term health outcomes. Routine hospital care often causes significant disruption in sleep-wake patterns that is further compounded by loss of personal control of health information and health decisions.

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We wished to evaluate measures directed at improving circadian rhythm and access to daily health information on hospital outcomes.

Methods: We evaluated 3,425 consecutive patients admitted to a medical-surgical unit

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comprised of an intervention wing (n=1,185) or standard control wing (n=2,240) over a 2.5-year period. Intervention patients received measures to improve sleep that included

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reduction of nighttime noise, delay of routine morning phlebotomy, passive vital sign monitoring, and use of red-enriched lighting after sunset, as well as access to daily

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health information utilizing an inpatient portal.

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Results: Intervention patients accessed the inpatient portal frequently during hospitalization seeking personal health and care team information. Measures impacting

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the quality and quantity of sleep were significantly improved. LOS was 8.6 hours less (p=0.04), 30 and 90-day readmission rates were 16% and 12% lower, respectively (both p≤ 0.02), and self-rated emotional/mental health was higher (69.2% vs. 52.4%; p=0.03) in the intervention group compared to controls.

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Conclusions: Modest changes in routine hospital care can improve the hospital environment impacting sleep and access to health knowledge, leading to improvements in hospital outcomes. Sleep-wake patterns of hospitalized patients represent a

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potential avenue for further enhancing hospital quality and safety.

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Funding Source: None

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IRB: This project was reviewed by the institutional IRB and was not considered human subject research based on the 45 CFR 46.102(d) definition of research, but rather a

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quality assessment and improvement activity (QA/QI) as part of standard healthcare operations in the local setting. As a result, there was no registration on ClinicalTrials.gov.

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Introduction Recovery from hospitalization includes recuperation from the acute illness leading to admission but also recovery from the physiologic disruption created from the

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environment of hospital care.1 This secondary condition has been called post-hospital syndrome, and has been defined as an acquired, transient period of vulnerability

derived from the allostatic and physiologic stress that patients experience during

hospitalization.1 During hospitalization, patients are frequently deprived of sleep,

almost total loss of personal control.

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experience disruption of normal circadian rhythms, become deconditioned, and have

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Sleep disruption is well documented and can impact multiple organ systems including immune function, coagulation, physical function and coordination, cognitive

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performance and metabolism.1-3 Disruption in circadian rhythms impact daily cellular protein expression, and significantly influence clinical outcomes, from timing of wound

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healing to surgical outcomes.4-6

Loss of personal control is common during hospitalization and is so profound that being

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a hospital patient has been called “one of the most disempowering situations one can experience in modern society”.7,8 In a survey of hospital patients, ninety percent of respondents wanted to review their hospital medication list, but only 28% were given the opportunity.8,9 In another study, only 32% of patients could correctly name even one of their hospital physicians.8,10

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The purpose of this investigation was to examine the impact of interventions focused on improvements in the quality and quantity of sleep as well as enhancing the patient’s control and understanding of healthcare knowledge and decisions. The outcomes

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evaluated included length of stay, hospital readmission, ICU transfers, and subjective measures of well-being.

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Methods

We prospectively evaluated hospital outcomes in 3,425 consecutive cardiovascular patients admitted to available beds on a medical-surgical floor consisting of a 15-bed

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intervention wing (n=1,185) or a standard 37-bed control wing (n=2,240). All patients were admitted to non-critical care beds capable of telemetry when ordered, and bed

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selection was based on solely on bed availability; bed control had no insight into the care delivery process in either wing. The control wing received standard of care as per

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hospital routine. 


The intervention wing utilized specific measures to improve sleep patterns including the

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monitoring and reduction
of nighttime noise, delay of routine morning phlebotomy, and use of red-spectrum lighting after sunset during routine nighttime checks.11,12 Noise levels were monitored in hospital corridors outside patients rooms, and a silent visual notification system was displayed in hallways to hospital personnel when noise levels after-hours exceeded 65db, which corresponded to approximately 30db in patient

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rooms with the door closed. Total nighttime noise burden was defined as the duration of time (minutes) when the decibel level exceeded 65 db. Laboratory services were instructed to delay all routine phlebotomy (non-stat, non-timed) until after 6:00 AM. Reports outlining each of these measures were provided each morning and evening to

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hospital care-teams and feedback was solicited to identify issues (i.e. any source of

noise) with recommendations on methods to eliminate disturbances that could impact sleep quality. An additional red-spectrum light was installed near the bedside to provide

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nursing an alternative to standard white lights when performing nighttime assessments. Vital signs including heart rate, blood pressure, respirations, temperature, and oxygen saturation were collected passively and unobtrusively using FDA approved wireless technology worn on the wrist (Sotera Visi Mobile®) that recorded data directly to the

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electronic medical record (Epic Systems Corporation) at one-minute intervals.13,14

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Nursing was alerted to vital signs that were considered abnormal via machine-to-nurse

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secure messaging via Sotera’s Insight app to an iPhone (Apple Inc.) carried by each nurse.

Each patient received an iPad (Apple Inc.) on admission, enabled with the inpatient

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portal, MyChart Bedside® (Epic Systems Corporation). The Health Insurance Portability

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and Accountability Act (HIPAA) secure app identifies the patient’s treatment team and includes pictures as well as brief bios of each provider and nurse rendering care to the patient. The app also provides detailed information regarding the patient’s active medications, education on the acute illness under treatment, daily results of labs, radiology and vital signs, as well as the schedule of diagnostic tests planned for the day.

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Patients can record conversations with their attending physician during rounds for playback later for themselves or family members who may not have been present.

Subjective measures were assessed using the Hospital Consumer Assessment of

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Healthcare Providers and Systems (HCAHPS) following discharge. Disease burden was assessed using the age-adjusted Charlson comorbidity index with higher scores indicating greater comorbidity.15,16

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Statistical analysis was performed using SPSS version 16.0 (SPSS Inc., Chicago, Ill.). Results are expressed as mean standard deviation, or as n (%) where appropriate. Analysis of differences between groups was performed using Student’s t test for

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continuous variables, and chi-squared test for categorical variables. Median

Results

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comparisons were made using Mann-Whitney.

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The study cohort consisted of 3,425 consecutive patients from March 2015 to October

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2017. The mean age of the study cohort was 64±16 years, 57% were male, and geometric mean length of hospital stay was 5.9 days (142 hours). The median Charlson index score was 6.0. Admitting services included cardiology (41.5%), hospital medicine (31.8%), heart failure/heart transplant (22.0%), surgery (3.2%), with the remaining 1.5% being various other services. Hospital physicians were surveyed and there were no

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reported delays or alterations in workflow as a result of the intervention. The intervention cohort was slightly older (mean age 66.2 ±15.2 versus 63.2 ±16.1 years, p<0.001), but there were no other significant differences in sex, race, creatinine, body

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mass index (BMI), or Charlson index score when compared to controls (Tables 1 & 2).

Inpatient portal use was frequently engaged, utilized in 70% of patients, with the

average patient accessing information multiple times during hospitalization. The most

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frequent option assessed was review of individual health metrics (labs, vitals, etc.),

followed by care team information, schedule of diagnostics/procedures, medication administration details, and patient prescribed education (Table 3).

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Table 4 compares outcome measures between patients in each of the two groups. The

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intervention was successful in improving measures that impact sleep quality and duration: nighttime noise burden fell by 31% (p = 0.04), and phlebotomy time delay

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provided the opportunity for an additional 1.2 hours of sleep (p<0.001). Hospital length

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of stay averaged 8.6 hours less in the intervention group (-6%, p=0.04), while mortality and clinical deterioration requiring ICU-transfer remained unchanged. Both 30-day and

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90-day readmission was significantly lower in the intervention group (-16%, p=0.02; 12%, p=0.009, respectively), and patients with 2 or more hospital admissions, 90 days after discharge trended lower (-14%, p=0.06). Patient reported measures rating emotional/mental health as “very good or excellent” were higher (+32%, p=0.03), and the need for medicine to treat pain trended lower (-38%, p=0.07) in the intervention

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group.

We further evaluated the clinical impact of the intervention based on tertiles of Charlson scores (Table 5). There were no differences in mortality, ICU transfers, and LOS

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between intervention and control patients within each Charlson group. There were

however significant differences in both 30 and 90-day readmission rates in patients with Charlson scores < 5. Compared to controls, intervention patients demonstrated a 34%

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reduction in 30-day readmission (17.9% vs. 11.8%; p=0.01) and a 33% reduction in 90-

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day readmission (30.7% vs. 20.7%; p<0.001).

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Discussion

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There are several key findings from this investigation. First, provided the opportunity, the majority of patients and their families will access information to better identify

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members of their care team as well as details regarding their on-going medical status including active medications, upcoming schedule of diagnostic testing, and recent test

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results. Second, improvements in the conditions for sleep, as well as measures to enhance personal control of healthcare knowledge can be easily implemented in the routine environment of hospital care without significant disruptions in operational workflows. Finally, interventions designed to enhance personal control of health information and improve intrinsic circadian rhythms can lead to significant

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improvements in clinical outcomes (re-hospitalization), operational measures (length of stay), and patient well-being.

The role of chronobiology in health is generally underappreciated during routine

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hospital care, however circadian rhythms have been demonstrated to modulate a wide range of health effects. More than 43% of all protein coding genes are regulated by the circadian clock, thus influencing multiple physiologic parameters including immune

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function, blood pressure, hormone production, efficacy of medication, wound healing

and surgical outcomes.2,4,17,18 For instance, influenza vaccination administered to elderly patients in the morning generates a significantly greater antibody response than does afternoon vaccination.19 Burn injuries suffered in the daytime heal significantly faster

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than similar injuries incurred at night.5 Aortic valve surgical patients experience better

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clinical outcomes when surgery is performed in the afternoon rather than the morning. 6 Acute and chronic disruption of circadian rhythm has also been linked to a wide range of

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adverse health outcomes. Chronic shift work is known to increase the risk for diabetes,

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gastrointestinal disorders, cardiovascular disease, lipid disorders, and cancer such that in 2007, the World Health Organization (WHO) declared shift work a carcinogen.2,20-22

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The acute effects of just a one-hour change in daylight savings time include an increase in myocardial infarction, stroke, automobile accidents, and accidents with fatalities.23-26 Yet in spite of a growing body of evidence demonstrating the relevance of circadian functions in daily health, routine hospital care often results in major and often unnoticed disruptions of the sleep-wake cycle.

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In this study, control patients underwent daily phlebotomies during sleeping hours as part of routine hospital care, and not uncommonly, vital sign assessments as well. Although this may be necessary for clinical care in specific cases, most non-critical

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patients can have these procedures performed exclusively during waking hours. There were no adverse clinical consequences from delaying routine phlebotomy until after 6:00 AM in the intervention group, and vital signs were comfortably obtained non-

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obtrusively and non-invasively through the night using currently available technology.

Additionally, a more subtle form of circadian disruption can take place when checking patients after hours using standard lighting.11,12 When exposed to even small amounts

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of white light (blue and blue-green), intrinsically photosensitive retinal ganglion cells

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(ipRGCs) signal the suprachiasmatic nucleus to reset circadian clocks, thus altering timed expression of numerous biologic events.27-30 The ipRGCs are most sensitive to short-

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wavelength blue and blue-green light and are less sensitive to red or orange-enriched

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light.20,30 By substituting blue-enriched light with red-enriched light after hours, we likely

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blunted stimulation of ipRGCs, thus reinforcing intrinsic circadian rhythms.

Hospital noise is also a contributing factor for sleep disruption and elevated levels of hospital noise are directly correlated to sleep loss.31-33 Hospital noise has been reported as high as 67db in the intensive care unit and 42db in medical and surgical wards, far exceeding the 30db nightly target for patient rooms recommended by the WHO.32,34 Our

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intervention included sound monitoring with silent alerts to hospital personnel when inroom noise levels exceeded the WHO recommended levels. Additionally, daily feedback from care teams led to workflow changes that resulted in progressive reduction in the overall nightly noise burden. These measures taken together enhanced the conditions

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for better sleep health, creating a true patient-centered environment of care.7,35,36

Engaging patients in their healthcare has recently become a focus of great interest.37

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The Institute of Medicine (IOM) recommends that patients have access to a ‘free flow of information’ and clinical knowledge, enabling them to be the ‘source of control’ in making healthcare decisions.7,8 This has never been more important than in the hospital setting, which can be an unfamiliar and isolating environment filled with anxiety and

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unanswered questions, and described as ‘one of the most disempowering situations one

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can experience in modern society’.8 Hospitalized patients experience significant knowledge gaps, and desire greater understanding of their clinical status, medications,

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and care team information, but only a minority are provided the opportunity to close

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these gaps.8-10 In contrast, efforts that augment transparency and flow of information led to enhanced patient satisfaction, and improved clinical outcomes including a

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reduction in readmission.8,38,39 Our intervention resulted in higher levels of emotional and mental health as measured by HCAHPS as well as improvement in clinical outcomes. Although, our study incorporated several interventions simultaneously, enhancing personal control likely contributed to the overall improvements described.

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Finally we demonstrated that the intervention reduced 30 and 90-day readmission primarily in patients with lower Charlson scores. There are two possible explanations for this finding. First, it is possible that the intervention was strong enough to blunt the effects of hospital toxicity in patients with less comorbidity, but was less effective in

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overcoming these adverse effects in patients with a greater burden of illness and thus susceptibility. Secondly, it may indicate that the underlying pathology of multiple

comorbidities is the primary driver of readmission, diminishing the additional impact

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imposed from the environment of hospitalization.

This study has several limitations worth noting. First, this was not a randomized trial. Patients were allocated to either group based solely on bed availability as per routine

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hospital practice, and the investigators had no influence on bed or group assignment.

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However, because of the large sample size and minimal differences identified between groups at baseline, we feel that the outcomes were not biased. Second, this was

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performed at a single site, and other investigators should confirm our results. Finally,

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we applied two important interventions simultaneously (enhancement of sleep and

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personal control) and our outcomes reflect the effects of the combined intervention.

In summary, modest patient-centered interventions that focus directly on enhancing access to health knowledge in conjunction with improvements in the hospital environment impacting sleep quality, can be easily incorporated in modern hospital

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practice and lead to meaningful improvements in quality, safety, cost, and patent

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satisfaction.

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Table 1 Demographics of the intervention and control groups. Control (n=2240)

P-value

Age (years)

66.2 ± 15.2

63.2 ±16.1

<0.001

Males (%)

56.7%

58.4%

0.34

Black (%)

38.5%

40.0%

0.39

White (%)

59.2%

57.3%

0.30

Hispanic (%)

1.1% 6.0

1.7%

0.17

6.0

0.70

1.5 ±1.4

1.4 ±1.3

0.52

Body mass index (kg/m2)

29.2 ±8.0

29.3 ±7.6

0.63

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Creatinine (mg/dl)

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Charlson index (median)

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Intervention (n=1185)

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Characteristic

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Table 2 Age-adjusted Charlson comorbidity score distributions between intervention and control groups

Control

Intervention

p-value

0-1

5.3%

5.1%

0.76

2-3

16.2%

14.5%

0.19

4-5

19.7%

21.4%

0.23

6-7

22.4%

21.4%

0.51

≥8

36.5%

37.6%

0.52

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Charlson Index

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Table 3 Average usage of the inpatient portal (Epic MyChart Bedside) per admission Activity

Frequency per Admission 0.62

Obtain care team information

0.58

Load schedule of upcoming diagnostics

0.51

Get medication administration details

0.50

View patient prescribed education

0.45

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Review health metrics

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Parameter

Intervention

60.3±398.2

41.7±335.3

-31%

0.04

4:53 AM

6:04 AM

1:11

<0.001

145.1±190.2

136.5±144.4

-6%

0.04

9.9%

8.4%

-15%

0.16

0.7%

0.7%

0%

0.99

22.4%

18.8%

-16%

0.02

39.0%

34.5%

-12%

0.009

≥ 2 admissions over 90 days

17.3%

14.9%

-14%

0.06

52.4%

69.2%

32%

0.03

53%

33%

-38%

0.07

Night noise burden (minutes) Morning phlebotomy time

Hospital length of stay (hours)

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(mean)

ICU-transfer

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30-day readmission

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In-patient mortality

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90-day readmission

Emotional/Mental health (rating “very good/excellent”) Medicine needed for pain (rating)

Change

P-value

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Control

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Table 4 Outcome measures in intervention and control groups.

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Table 5 Differences in outcomes between intervention and control patients based on Charlson score.

5-7 (n=1,102)

≥8 (n=1,262)

90-day

Readmission

Control

Interv

P

Control

Interv

P

17.9%

11.8%

0.01

30.7%

20.7%

<0.001

134.8±145.2 133.0±178.4 0.87

20.9%

19.8%

0.69

38.5%

34.2%

0.16

154.9±217.7 145.9±220.7 0.52

27.5%

23.6%

0.13

46.5%

45.8%

0.82

Control

Interv

P

145.2±198.0 131.3±145.1 0.16

AC

CE

PT

ED

M

Interv = intervention, LOS = length of stay

LOS (hours)

CR IP T

<5 (n=1,061)

30-day Readmission

AN US

Charlson score

24