THE EDWARD J. STEMMLER MD€¦ · mentorship, what constitutes “supervision” is not clearly defined. Resident oversight by attending physicians on the general inpatient medical

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THE EDWARD J. STEMMLER, MD

MEDICAL EDUCATION RESEARCH FUND

2014‐2015 INVITED PROPOSAL

Title: Assessment of Resident Decision Making and Patient Safety: A

Randomized Trial of Inpatient Medical Attending Supervision of Trainees

Primary Investigator: Kathleen M Finn M.D. M.Phil

Co‐Investigators: Christiana Iyasere M.D., M.B.A.

Joshua Metlay M.D., PhD., Hasan Bazari M.D,

Jay Vyas M.D., PhD., Yuchiao Chang, PhD.,

and Elyse Park PhD., MPH.

School: Harvard Medical School

Massachusetts General Hospital

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A. Letter of Intent Application. (Cover Sheet)


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Letter of Intent

Study Objectives and Research Question/Hypothesis

Graduate physician training is based the apprenticeship model where residents provide care to

patients under the supervision of a senior physician. Residents gain increased patient care

responsibility, learn critical thinking and make medical decisions with a gradual reduction in

supervision as the trainee develops mastery. In this model, performance is increased via

explicit instruction from a learned mentor or teacher to allow individualized diagnosis of errors,

informative feedback and remedial part training. (1)

Despite the historical legacy of the apprenticeship model and the importance of clinical

mentorship, what constitutes “supervision” is not clearly defined. Resident oversight by

attending physicians on the general inpatient medical wards varies widely. For example, some

attendings independently review all laboratory values and imaging and impose minor changes

in treatments, others do not. The right balance between autonomy and supervision to promote

both learning and ensure excellent patient care is unknown and difficult to achieve. We

propose a study that begins to investigate these questions – what is a reasonable level of

resident oversight? What are the consequences, both intended and unintended, of increased

resident supervision on the medical wards? What models can we employ to assess these

outcomes?

Following the death of Libby Zion, the Bell Commission cited both fatigue and inadequate

supervision of residents as contributing factors to her untimely death. (2) As a result, both New

York State and the Accreditation Council for Graduate Medical Education (ACGME) focused on

resident work hour limitations in an attempt to improve patient safety by reducing medical

errors. However, duty‐hour reform has not demonstrated the improved patient safety

outcomes anticipated, and work hour restriction has raised questions about a decline in

educational opportunities. (3, 4) \

Given the fundamental importance of improving patient safety, the emphasis is now shifting

from hours worked to the level of supervision of residents. If improved duty hours have not

reduced medical errors and improved patient safety, perhaps increased attending supervision

will? In response to these concerns, some residency programs have intensified senior clinician

involvement on the medical wards. In these new models, attendings now fully participate in

both new patient presentations and old patient work‐rounds, are present on the wards for

most of the day and are engaged in all details of patient care. Residents’ decision making is

monitored, their plans are closely reviewed, and attendings are directly involved with patients

and their families.


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Deeper attending involvement in patient care and medical decision making seems to be a

logical next step to improve patient safety. The underlying assumption is – more supervision,

better patient outcomes and resident training. Yet two recent studies comparing increased

nighttime Intensive Care Unit supervision to prior more limited staffing models found no

difference in mortality or patient safety outcomes. (5, 6) Similarly, heightened attending

involvement in medical decision making may be at odds with the way residents learn best.

Adult learning theory emphasizes adults are self‐directed learners and best discover knowledge

for themselves without being told. (7) Many physicians report that independent decision

making was crucial for their development as physicians and maturation of clinical thinking. (2)

Some would argue closer attending supervision may be detrimental to residents’ education, a

theme echoed in a recent perspective piece in the New England Journal of Medicine which

raised concerns about the effect of increasing levels of supervision on resident education and

critical thinking. (2)

It is within this context that we propose to investigate the hypothesis that increased attending

supervision in resident decision making improves patient safety

Rationale for Proposed Research

Massachusetts General Hospital is a 1100 bed tertiary/quaternary medical center. The Internal

Medicine Residency Program has 185 residents who rotate through both outpatient clinics and

inpatient wards during their tenure. On the inpatient wards the residents interface with 30 core

teaching faculty, those who have distinguished themselves as medical teachers and are fluent

in inpatient care.

The general medical inpatient service has a mixed model of supervision. For new admissions

the attending is deeply involved in initial critical thinking and decision making. Attendings and

residents round together for two hours every morning examining and discussing the new

admissions. However, resident decisions regarding ongoing management and care of existing

patients on the service occur independently of the supervising clinician. After the new patients

are presented and discussed with the attending, the residents go on bedside work rounds to

evaluate the existing patients without the attending. During these bedside work rounds

residents examine all the existing patients, discuss updates, make decisions about plans for the

day, call consults and enter orders. The attending for the team briefly provides advice later in

the afternoon to help adjust and refine treatment plans on these existing patients.

To investigate whether increased attending supervision in resident decision making improves

patient safety, we plan to have these 30 core faculty join bedside work rounds with the

residents. Since faculty members will attend on service multiple times during the study period,

we will randomize all attendings to both the current system (usual care) and the increased


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supervision model – participating in work rounds (intervention). Attendings will serve as their

own control. Will this increased supervision improve medical decision making by residents and

reduce medical errors?

To better understand the effects of attending input and participation on resident decision

making during work rounds we will assess the following:

Does attending presence influence: Metric of Measurement

Patient treatment plans Change in frequency of written orders

Time spent per patient at the bedside and in

discussion

Time motion study of work round length and

participant location

Quantity of resident input into decision

making

Vocalization of residents during work rounds

Quality of resident input into decision making Blinded review of work round transcripts by

established experts in the field

Resident perception of learning environment,

quality of care and self evaluation of

competency

Survey and focus groups

Attending perceptions of learning

environment, resident competency and

patient care

Survey and focus groups

Patient outcomes Medical errors, preventable and avoidable

adverse events during time of study, cost per

patient, # ICU transfers, LOS and # of pre‐noon

discharges

Traditionally, resident knowledge has served as a surrogate for overall competency, but

knowledge alone provides limited insight into how residents make decisions and the quality of

the decisions that are made. It is fundamentally physician decision making that addresses

competence. This research study will directly asses resident medical decision making, the

consequences of attending participation in this process and the effect on medical education

and patient outcomes.


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Given there are no prior studies assessing the impact of attending supervision on resident

critical decision making and patient outcomes in medicine, we believe this study would be

unique. We will utilize novel methods to collect data including time motion studies, direct

observation and review of transcripts from work rounds for analysis. This study is of particular

import as we strive to better understand what environments drive optimal decision making and

resident training. If increased supervision is mandated by the ACGME without research to

confirm its value to both patient safety and resident education, the outcome could be increased

costs to the health care system and possibly less competent physicians. Alternatively, through

better understanding of the inputs to optimal performance and the balance between

supervision and autonomy we can focus our efforts and resources on proven interventions.

Description of Methods

To understand the effects of attending participation on work rounds (the intervention) we will

randomize supervising attendings to two weeks on service with a medical team where they

attend work rounds and two weeks on service on the traditional model (attending participation

on new attending rounds only with post hoc advice for previous patients). All teams will consist

of two attendings, five interns and one junior resident. The study will be done from November

to late June 2015 in order to avoid the “July effect” where it is suspected there are more near

misses due to resident inexperience. (8) Given that approximately 80 novel patients are

admitted to a team per month, over the ensuing eight months over 1200 resident/attending

discussions of patient cases will be evaluated.

The primary outcome will be medical errors, preventable and avoidable adverse events and

near misses per 100‐admissions. These will be collected by two clinical research nurses through

chart review, review of all orders, daily solicited error reports from residents and attendings

and a review of all formal incident reports. Similar to a recent paper assessing rates of medical

errors and preventable adverse events during handoffs, all incidents will be classified as adverse

events, non‐intercepted potential adverse events, intercepted potential adverse events and

error with little potential for harm. (8) All recorded events will be blinded and adjudicated by

three research physicians as to whether they are real errors, adverse events and near misses.

Disagreements will be resolved by discussion.

Secondary outcomes will include changes in medical orders between 12pm and the 7pm (when

the team signs out). This should reflect whether the teams had to reverse the orders they wrote

during morning bedside work rounds. We will also assess cost per patient. This should reflect

whether closer supervision during decision making on work rounds reduces unnecessary orders

and helps reduce expensive test ordering. Other patient safety results will be obtained from

hospital data including length of stay, pre‐noon discharges, transfers to the ICU and

readmissions. Additional secondary outcomes include patient and family satisfaction with MD


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communication (part of the hospital collected post discharge survey results). We will survey

residents about perception of autonomy and satisfaction and perceptions about education. We

will also survey faculty about their perception of resident autonomy and education. We will

asses both the residents and faculty’s perception of how frequently they believe faculty input

changed plans on new and old patient work rounds.

Finally we plan to do a time motion study of work rounds. We will record actual time of work

rounds to learn whether the presence of an attending increases the length of rounds. Also

recorded will be counts of who is speaking during bedside work rounds and how often the

intern is interrupted. We will also evaluate transcripts of the work rounds for resident decision

making thought processes.

All of these outcomes will assess and probe resident decision making and its impact on patient

safety testing the hypothesis that increased attending supervision in resident decision making

improves patient safety.

Key References

1. Ericsson, KA, Krampe RT and Tesch‐Romero, C. The Role of Deliberate Practice in the Acquisition of Expert Performance. Psychological Review, 1993, Vol 100, No 3 363‐406.

2. Halpern S and Detsky A. Graded Autonomy in Medical Education – Managing Things That Go Bump in the Night. NEJM. 2014;370;12:1086‐1089.

3. Volpp, K, Rosen A, Rosenbaum P et al. Mortality Among Hospitalized Medicare Beneficiaries in the First Two Years Following ACGME Resident Duty Hour Reform. JAMA. 2007;298(9):975‐983

4. Desai S, Feldman L, Brown L et al. Effect of the 2011 vs. 2003 Duty Hour Regulation – Compliant Models on Sleep Duration, Trainee Education, and Continuity of Patient Care Among Intern Medicine House Staff. JAMA Intern Med. 2013;173(8):649‐655.

5. Kerlin M, Small D, Cooney E et al. A Randomized Trial of Nighttime Physician Staffing in an Intensive Care Unit. NEJMB 2013;368:2201‐9.

6. Garland A, Roberts D, GraffL. Twenty‐four Hour Intensivists Presence: A Pilot Study of Effects on Intensive Care Unit Patients, Families, Doctors and Nurses. Am J Respir Crit Care Med 2012;185:738‐43.

7. Kaufman, D. Applying Educational Theory in Practice. BMJ. 2003. 326(7382):213‐216.

8. Starmer A, Sectish T, Simon D et al. Rates of Medical Errors and Preventable Adverse Events Among Hospitalized Children Following Implementation of a Resident Handoff Bundle. JAMA. 2013;310(21):2262‐2270.


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B. A Description of Changes to the Proposed Research

We have made the following changes:

1. We now plan to use one research nurse instead of two.

2. The study dates will now be Sept 30, 2015 to June 7, 2016.

3. In the proposal we have clarified many of the outcomes.

4. We will be submitting our IRB application in early February.


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C. Table of Contents

A1. Application Cover Sheet Page 2

A2. Letter of Intent Page 3

B. Description of Changes Page 8

C. Table of Contents Page 9

D. Proposal Narrative Page 10

E. Budget Form Page 25

F. Budget Narrative Page 26

G. Project Timeline Page 27

H. Primary Qualifications Page 28

I. Biographical Data Forms Page 30

J. Appendices

References Page 43

IRB Page 44

Non Profit Status IRS 501(c)(3) Page 45


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D. Proposal Narrative

An Assessment of Patient Safety in Resident Education: A Randomized Trial of Inpatient Medical Attending Supervision of Trainees.

1. Background Information

Graduate physician training has been based on the apprenticeship model where residents

provide care to patients under the supervision of an attending physician. As trainees gain patient

care experience they are given increasing responsibility with a gradual reduction in supervision.

This model of progressive independence allows clinical oversight as trainees master clinical

reasoning and decision making skills. The goal is to develop competent and independent

practitioners. [1] This progressive supervision is provided to residents as a mixture of scheduled

time with an attending physician and independent work time. In a paper defining degrees of

supervision, Kennedy et al call this traditional model “routine oversight.” [2] In most training

programs routine oversight consists of scheduled morning attending rounds where cases are

presented to the supervising physician for discussion and correction of residents’ plans.

Historically, the rest of the time trainees worked independently with the ability to call the

supervising physician if needed. [3] Much of the independent time occurred at night and on the

weekends when attending physicians were not in the hospital. [4]

In the last decade this independent work time has been scrutinized largely driven by the

patient safety movement. This traditional model of supervision was first called into question after

the Bell Commission investigation into the death of Libby Zion in a New York teaching hospital.

The investigation found both resident fatigue and inadequate clinical supervision as contributing

causes in the death. [5]


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With pressures from the public, government and patient safety advocates the

Accreditation Council for Graduate Medical Education (ACGME) and the Institute of Medicine

(IOM) focused new policies on resident duty hours. The goal was to improve patient safety by

reducing medical errors through restriction of work hours; less fatigued residents would make

fewer mistakes. [3, 6] Starting in 2003, and again in 2011, resident work hours were limited.

However, duty-hour reform has not demonstrated the improved patient safety outcomes

anticipated. [7-9] A study of Medicare data found no mortality difference in medical or surgical

patients after the 2003 work hour change. [7] Following the 2011 changes, a study of 2,323

medical interns noted they worked fewer hours, but did not gain additional sleep and self-

reported more medical errors. [9] A second study showed an increase in patient hand-offs and a

decrease in both continuity of care and educational opportunities.[8]

Without the patient safety outcomes hoped for, there is now more focus on the second

recommendation of the Bell Committee: increased supervision. But will increased clinical

supervision improve patient safety? A small body of literature demonstrates benefits from

increased supervision or complications from its absence. [2, 10-12] One study found increased

resident compliance with emergency room guidelines when residents were supervised.[10] Here

supervision was defined by whether the attending wrote a separate note. A study in anesthesia

showed a reduction in complications during intubation when an attending was present. A surgical

trauma review noted missed radiological diagnoses without attending supervision. [11, 12]

Similarly, a study in primary care demonstrated that attendings judged patients to be more

seriously ill and reported a change in management for 27% of the cases after having seen the

patients.[13]


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Survey research looking at the impact of resident supervision from the trainee perspective

suggests benefits from a higher degree of supervision. A national survey of residents in multiple

specialties asked residents how often they cared for patients without “adequate supervision,”

with 21% of 3,604 residents reporting inadequate supervision at least once a week.[14] Better

supervision correlated with positive ratings of learning, increased time with attendings and better

residency experience. In four studies on increased faculty presence on the wards, either in the

afternoon or overnight, residents reported increased satisfaction with both faculty and education.

[15-18] These studies conclude that increased supervision would enhance education and assume

it would improve patient safety.

The patient safety movement, lead by the IOM with support from the government,

medical boards, clinical educators and the public has called for increased supervision. Some

policy changes around supervision have already been implemented. The 2011 ACGME work-

hour changes included a requirement that “the program must demonstrate that the appropriate

level of supervision is in place for all residents who care for patients.”[19] One-third of U.S.

hospitals increased nighttime intensive care unit (ICU) supervision. [3] And yet early studies on

this new policy have not shown patient safety benefits. [20, 21] A one year ICU study found no

change in length of stay or mortality especially for those patients admitted overnight.[20] An

accompanying perspective piece in the New England Journal proposes that we should have a

better understanding of the clinical and educational tradeoffs between supervision and resident

autonomy before blindly implementing policies. [3]

What is known about medicine’s model of clinical education and supervision? In a

review of the medical, social science and educational literature, Kennedy notes there is little

evidence to demonstrate the efficacy of the current graduate medical model of education.[1] This


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progressive supervision model appears to have developed intuitively. In a review of effective

supervision in clinical practice settings, Kilminster and Jolly conclude “(clinical supervision) is

probably the least investigated, discussed and developed aspect of clinical teaching.” [22] While

it is commonly believed supervision is critical in the acquisition of clinical skills and

professional development of trainees, it is difficult to know what actual components of

supervision matter. The Kilminster review concludes by asking, “In what circumstances is

supervision necessary? What sort of supervision should this be? “What is the optimal length and

frequency for supervision?” [22] There are indeed the questions that we seek to answer in the

proposed study.

An evaluation of models of supervision needs to consider not only the impact on patient

outcomes but also the impact on physician skill development. Is there harm in too much

supervision? Many physicians recall their independent work time as formative in their

development as clinicians. The expertise literature supports this idea. Learners must be engaged

in active decision making and take responsibility for the results of their actions in order to

integrate new information into their understanding of situations. [1] There needs to be some

degree of independence in order to progress to expertise. Educational theory notes that learning

takes place when learners are challenged to work beyond the level at which they comfortable and

self directed learning occurs when there is appropriate space between teacher and learner. [4]

And sociology literature has illustrated the limitations when learning and evaluation occur at the

same time; a common practice in clinical supervision. Studies in medical students reveal they

disguise their lack of knowledge and do not ask questions in order to portray competence. [23]

In Kennedy’s review she notes excessive supervision without progressive independence may

hamper progression to competent practitioner.[1] A balance between supervision and autonomy


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is required to facilitate resident’s development. In the short term limiting autonomy might

improve patient safety, but in the long term could have unintended consequences of creating

physicians who are not ready for independent practice. The question is what is the right amount

autonomy without compromising patient safety?

The growth of hospitalists over the last decade has provided more faculty presence on the

wards expanding supervision beyond “routine oversight”. Hospitalists are now more involved in

patient care details and double check residents’ work. This is defined as “responsive oversight”

in the framework of supervision created by Kennedy et al. [2] Hospitalists also provide direct

patient care without involvement of the resident and practice more “backstage oversight” defined

as reviewing all the patient’s care details without the trainee’s awareness. A study on the

introduction of hospitalists in a pediatric hospital, where attendings gave more “responsive

oversight” and did direct patient care, found the interns reported learning more and still felt they

could make decisions independently, but upper level residents reported a decrease in their

knowledge and supervisory skills and a loss in their ability to make independent decisions. [18]

This study raises questions about the optimal type of supervision and when it should be applied.

In this context it is clear that there is limited evidence as to the appropriate balance of

clinical supervision and autonomy for both patient safety and educational purposes. Multiple

medical educators have expressed the need for studies evaluating types of supervision and its

related outcomes. [3, 4, 22] With this is mind, we propose to study the effect of additional

attending “responsive oversight” on resident medical teams in terms of both patient safety and

resident learning. Given that the mission of the National Board of Medical Examiners is to

“protect the health of the public through the state of art assessment of health professions”,

clinical supervision clearly falls under this domain. Traditionally, resident knowledge has


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served as a surrogate for overall competency, but knowledge alone provides limited insight into

how residents make decisions and the quality of the decisions that are made. It is fundamentally

physician decision making that addresses competence. This research study will directly asses

resident medical decision making, the consequences of attending participation in this process and

the effect on medical education and patient outcomes.

2. Hypothesis or Research Question

Background: Currently our general medical inpatient service employs the model of “routine

oversight”. During the scheduled daily two-hour morning attending rounds new admissions are

presented at the bedside. These rounds focus only on new admissions to the medical team. After

attending rounds, a resident leads team rounds on all of the previously admitted patients without

the presence of the attending, identifying new medical issues, discussing ongoing problems and

reviewing the management and care of these existing patients. This is frequently referred to as

“work rounds”. The attending for the team independently sees and evaluates the previously

admitted patients and briefly provide advice to the supervising resident later in the afternoon to

help adjust and refine treatment plans. With this background, our research aims are:

Specific Aims:

1. To investigate whether a rounding model of increased resident supervision by

including attending physicians on work rounds (responsive oversight) in addition to new

patient rounds (routine oversight) compared to attending physicians on new patient

rounds only (routine oversight) result in improved patient safety? This will be measured

by a reduction in medical errors (primary outcome) and reductions in length of stay,

intensive care unit transfers, inpatient morality and costs (secondary outcomes). Our

hypothesis is that the increased supervision model will improve patient outcomes.


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2. To investigate whether a rounding model of increased resident supervision by

including attending physicians on work rounds (responsive oversight) in addition to new

patient rounds (routine oversight) compared to attending physicians on new patient

rounds only (routine oversight) affect resident autonomy, decision making and learning?

This will be assessed by the percentage of time of resident communication on work

rounds and length of work rounds (primary outcome). Secondary outcomes will include

resident, attending and nurse perception of education and autonomy and a qualitative

analysis of content of discussion on work rounds and reason for attending interruptions.

Our hypothesis is that increased supervision will not affect educational outcomes for

residents.

Outcomes:

To better understand the effects of attending input and participation on patient safety and

resident education and autonomy during work rounds we will assess multiple aspects of the

supervisor-resident-patient triad. (Table 1) Each aim, (1) patient safety and (2) education and

autonomy, will have its own primary and secondary outcomes. Given the complexity of the

relationship between supervision, resident education and patient safety, we believe it is necessary

to evaluate both aims and their outcomes during this study. The results of one aim cannot be

interpreted without the results of the other.

Patient Outcomes:

Our primary outcome of patient safety which will be assessed by recording medical

errors using the standard definition that medical errors are preventable failures in the process of

care. Medical errors will include preventable adverse events, near misses and errors with little or


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no potential for harm. Using an established surveillance process developed in several studies

evaluating medical errors in residency programs, we will measure the rate of medical errors per

100 admissions. [24-26] We will also collect mortality, length of stay, transfers to the intensive

care unit (ICU) and total costs, including the number of radiology studies as secondary

outcomes. Our hypothesis is “responsive oversight” will reduce medical errors, mortality, length

of stay, transfers to the ICU, costs and number of radiology studies as residents are supervised in

decision making.

Educational Outcomes:

To assess the effect on resident autonomy, decision making and learning, we plan to use a

mix methods approach during work rounds for both the intervention period (responsive

oversight) and the control period (routine oversight). Our primary outcome will be assessed by

the length of work rounds and the amount of time the resident is communicating during these

rounds. Using a time motion study of work rounds, both on the intervention and usual care

teams; we will measure length of work rounds and quantity of conversation by the resident,

attending and interns. Who is actually talking during the work rounds? Our secondary outcomes

will include both quantitative and qualitative components. At the conclusion of each 2 week

block, we will survey of residents, attendings and nurses about their perception of the learning

environment, autonomy and decision making and patient care. Given nursing also participate in

resident work rounds, their unique perspective as the patient advocate will be valuable. The

qualitative data collection will include content analysis of the conversations occurring during

work rounds. We will assess the conversational interactions around the following clinical areas:

(1) interpretation of the data (labs, vital signs, and physical exam), (2) identifying problems, (3)

generating differentials, (4) decision making or (5) teaching points. Which area is the attending


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participating in? These analyses will be conducted comparing conversations with and without an

attending present, to explore which areas the supervising resident participates. We will also

assess the reasons for attending interruptions on work rounds.

Table 1 Outcomes Does attending presence influence: Metric of Measurement Patient outcomes Primary

Medical errors: preventable adverse events, near misses and errors with little harm.

Patient outcomes Secondary

Mortality, # ICU transfers, LOS, cost of hospitalization and number of radiology studies.

Educational Outcomes Primary

Length of work rounds and time/percentage of resident communication during rounds.

Educational Outcomes Secondary - quantitative

Surveys of residents, attendings and nurses perceptions about learning environment, autonomy, decision making and care

Educational Outcomes Secondary - qualitative

Content analysis of discussion on work rounds and reasons for attending interruptions

3. Study Design and Methodology

Study Design: Our intervention is to expand supervision from “routine oversight” (attending

rounds on new patient only) to “responsive oversight” (attending rounds on new patients and

established patient work rounds). Since faculty members attend on service multiple times during

the study period, we will randomize all attendings to both the current system of “routine

oversight” (usual care) and the increased supervision model or “responsive oversight”

(intervention). In the intervention phase, the supervising physician will more actively participate

in work rounds, overseeing detailed resident discussions and decision making about existing

patients on the medical team.

We will conduct a randomized cross-over study, with each attending serving as his or her

own control. Faculty rotations are two weeks and they work with the same resident team for that

entire time. Faculty will be randomized to start with either the intervention or usual care for the


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duration of the two weeks for their first rotation during the study period and then “cross-over” to

the other study arm for their next two week rotation. (Figure 1).

Figure 1

Study Settings: Massachusetts General Hospital (MGH) is a 1100 bed tertiary/quaternary

medical center. The study will take place on the MGH general medical service which consists of

5 identical teams on similar nursing floors. Patients are randomly assigned to teams by the

admitting department based on bed availability. The study will occur September 30, 2015 to June

7, 2016. We plan to start in late September to avoid the “July Effect” of new trainees, a time

when we would expect more medical errors.[27]

Participants: The Internal Medicine Residency Program has 185 residents who rotate through

both outpatient clinics and inpatient wards during their training. Inpatient resident teams consist

of one resident, 5 interns and two attendings and care for 20-24 patients. Resident teams rotate

Responsive Oversight (+attending rounds, + work rounds)

Routine Oversight (+attending rounds, ‐ work rounds)

2 weeks 2 weeks

Attending A

AttendingAttending B

Attending

Intervention

Arm

Control A

rm


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every 2-4 weeks, with upper level residents working on this service 6-8 weeks a year and interns

working about 4 months a year. We anticipate the study will involve 30 upper level residents

and nearly all 85 interns. On the inpatient wards the residents interface with 20 core teaching

faculty, who have distinguished themselves as medical teachers and are fluent in inpatient care.

These 20 experienced clinician educators have a background in inpatient medicine and

frequently attend on service.

Attendings participating in this study will receive a one-hour training session on

“responsive oversight” with a discussion of expectations for joining work hours. Residents and

interns will receive an orientation to this process and will receive reassurances that the

measurement of medical errors will be blinded and there will be no consequences to their

reporting such errors. Nursing on the floors will receive the same orientation and reassurance.

Data Collection and Analysis:

Patient Outcomes: For the primary outcome of medical errors we will apply standard

definitions. [24, 25] Medical errors, as noted previously, are preventable failures in the process

of care and include: (1) preventable adverse events, (2) near misses (where the error was caught

before anything could happen) and (3) errors with little or no potential for harm. We will also

collect non-preventable adverse events, and since these events cannot be prevented, this event

rate should be similar in both arms. Using an established surveillance process, one trained

research nurse will review all medical records and orders on the medical teams, 5 days a week,

with Mondays review to include a review of the weekends. [24, 25] There will be a locked-box

on each floor where nurses and residents can anonymously submit possible medical errors and

near misses. The nurse will also ask the team each day about possible errors, as well as

pharmacy, and will check the hospital reporting system for events. All possible medical errors


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will be reviewed by two blinded physician investigators. They will independently classify each

event as a preventable adverse event, near miss, error with little potential for harm, non-

preventable adverse event or exclusion (not a medical error). The preventability of the adverse

event will be rated on a 4-point Likert scale: (definitely preventable, probably preventable,

probably not preventable, or definitely not preventable) which will be dichotomized into

preventable versus non-preventable before analysis. We will be following the methodology of

the IPASS study looking at medical errors in hand offs. [24] We will also collect severity of

harm using the National Coordination Council for Medication Error Reporting and Prevention

Index for Categorizing Errors. (MCC MERP). [28] Any disagreements in error assessment will

be summarized using a kappa statistic and resolved by discussion between the physician

reviewers. Secondary patient outcomes (morality, number of ICU transfers, length of stay, cost

of hospitalization and number of radiology studies) will be obtained from the hospital data base.

In the primary analysis, we will use an intention-to-treat approach for each patient. That

is, patients’ group assignment will be determined by the status of the first responding clinician

they encounter during the study period. We will compare the patient characteristics between

patients under routine oversight and patients under responsive oversight. The potential

confounding factors will be included in the regression model if any imbalance exists. We will

compare between the two groups using Poisson regression models for medical error rate, number

of ICU transfers, and number of radiology studies and quantile regression models for length of

stay and cost of hospitalization. We will use the mixed effects model approach to take into

account the clustering of patients within each responding attending and model the care team

(residents, interns and nurses) as random effects.


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In a secondary analysis, we will determine patient’s group assignment on a daily basis

according to the status of the assigned attending since patients’ hospitalization might span across

faculty rotations. Poisson regression models will be used to compare medical error rate between

the two groups with group considered as a time-varying variable.

We will conduct two pre-specified exploratory analyses. The first is looking at error rates

comparing the first 4 months to the last 4 months of the study. Studies on residents are

complicated by the fact they gain knowledge and improve through time. Our faculty will be

randomized throughout the year to try and mitigate this, but we plan to evaluate error rates based

on time of year. We will also compare error rates looking at the order in which attendings are

randomized. If an attending does the “responsive oversight” arm first, will this affect their

ability to return to “routine oversight”?

Educational Outcomes: For the primary educational outcome we will have a research assistant

join resident work rounds both on the intervention team and usual care team. For this time-

motion study, we anticipate they will join rounds approximately 5 times during a two-week

block. They will record rounds with permission granted by the resident team, nurse, attending

and patients. Using an iPad device, they will record the number of times and length each

individual speaks. The total length of these work rounds will be recorded. We plan to collect the

length of work rounds on all teams on weekdays. On the days the research assistant cannot join

rounds, they will ask the team for the start and stop time of work rounds. We will first examine

the distribution of the length of work rounds and time/percentage of resident communication

during rounds and perform variable transformations if necessary. These outcomes will be then

compared using a linear regression model with the Generalized Estimating Equations method to

take into account of the clustering within each attending.


23

For perceptions, we will email surveys to the residents, attendings and nurses at the end

of every two week rotation to evaluate their perception of autonomy, the learning environment,

decision making and quality of care of patients. Survey responses will be compared between the

two groups using regression models taking into account of the individual responder effect.

Qualitative Data Analysis: Using purposive sampling, a random selection of recorded work

rounds with and without attending participation will be transcribed. We will transcribe both the

intervention work rounds and usual care work rounds. Each transcript will be coded by the

physician investigators and will explore the content of the discussion, including: (1)

interpretation of data, (2) identification of active medical problems, (3) the generation of

differential diagnoses for the active medical problems, (4) decision making regarding plans for

each problem and (5) teaching points around active or theoretical problems. We will initially

review a subset of transcripts and develop preliminary codes. We will then apply these final

codes to our random sampling using NVivo 10 qualitative data analysis software. Coding will

continue until level of agreement (kappa > 0.80) is reached. We will resolve discrepancies by

reviewing the transcript data for context. We will evaluate which areas the attendings are

involved in, how often they speak and who makes the final decision for each problem. All

analyses will be conducted comparing findings on rounds with attendings and without

attendings.

In a prior study looking at attending interruptions on new patient presentations, the

researchers used the following 5 categories to classify interruptions by the attendings: (1)

Probing for further data, (2) prompting for expected sequence, (3) teaching around the case, (4)

thinking out loud and (5) providing direction. [29] We will use these categories for analyzing

attending interruptions.


24

Finally, we will explore whether there is a relationship between percentage of time

communicating on rounds, the content areas discussed, number of interruptions by the attending

and if any of these are related to medical error rates.

Sample Size: Given that each attending sees approximately 25 new admissions during each two-

week block, and all 20 attendings will be attending both in the usual arm and intervention arm,

we anticipate to enroll 500 patients in each arm. Since patients are clustered within each

attending, the inflation factor is 2.7 in an intra-class correlation coefficient of 0.07 and the

effective sample is 187 per group. Based on prior studies using the same surveillance methods

we anticipate 55 errors per 100 admissions from the routine oversight group and 33 errors per

100 admissions from the responsive oversight group, which only requires 178 patients per group

for 80% power and a 0.05 two-sided significance level. ([24, 26]

Conclusion: Given the limited number of studies assessing the impact of attending supervision

on resident decision making, autonomy and patient outcomes, we believe this study would be

unique. We will utilize a well established surveillance process to assess medical errors, a time

motion study, direct observation and a qualitative analysis of transcripts from work rounds. This

study is of particular import as we strive to better understand different aspects of supervision and

their affect on the development of independent and competence physicians. If increased

supervision is mandated by the ACGME without research to confirm its value to both patient

safety and resident education, the outcome could be increased costs to the health care system and

possibly less competent physicians. In order to ensure to the general public both short term and

long term patient safety, we need to find the right balance of supervision and autonomy through

proven interventions.


25

E. Project Budget Form

PERSONNEL‐ DIRECT COSTS Year 1 Year 2 TOTAL

Compensation (Not including fringe benefits.)

A. Kathleen Finn, MD, Principal Investigator $0 $0 $0

B. Research RN $73,873 $0 $73,873

B. Research Asst $23,400 $0 $23,400

C. Fringe Benefits $35,991 $0 $35,991

OTHER‐ DIRECT COSTS

A. iPad $600 $0 $600

B. Travel $0 $0 $0

C. Materials and Supplies $0 $0 $0

D. Consultants/Contractual (Include both honorarium and travel costs for consultants. Provide a breakdown in the Budget Narrative)

$0 $0 $0

E. NVivo Software ‐ 10 $2,500 $0 $2,500

PROJECT ADMINISTRATIVE CHARGES

(Limited to 10% of the amount of Total Direct Costs) $13,636 $0 $13,636

TOTAL PROJECT BUDGET $150,000 $0 $150,000


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F. Budget Narrative

Research Nurse Investigator: The clinical research nurse must be experienced in inpatient medicine and clinical medicine. He or she will be reviewing charts and medical orders searching for medical errors. He or she will also need to speak regularly with team members, nursing and pharmacy and review medical error reports. Given the identification of medical errors is a primary outcome for this study we anticipate hiring a more advanced clinical nurse investigator. At our institution the top rate is $70/hour. We anticipate he or she will need to work 8 hours per day. This person will be hired for 8‐9 months.

Research Assistant: This person will need to record work rounds for the qualitative component of the study, as well as measure the speaking time of each team member and total length of rounds. They will be transcribing the recordings in the afternoon. We will need someone with a college degree who can transcribe. At our institutions the lowest rate for a research assistant is $15/hour. This person will be hired for 8‐9 months.

IPad: This device will be used by the research assistant for both recording rounds and for counting speaking time. We will be searching or programming an App to help us with both the recording and counting components.

NVivo software: This commercial software is needed to qualitative analysis of content of work rounds.

Physician Investigators: The investigators’ time will be supported by Massachusetts General Hospital


27

G. Project Timeline

January 14, 2015 Submission of the Invited Proposal

February 3, 2015 IRB Submission to Harvard Medical School and Partners Healthcare

Summer, 2015 Hiring of Research Nurse and Research Assistant

Purchase of iPad and programming data collection application

Randomization of Faculty

September 2015 Training of Research Nurse and Research Assistant

Training of Clinical Faculty who will be attending on service

Orientation sessions for resident teams and floor nursing

September 30, 2015 Start of first 2 week block and beginning of study

October 2015 – September 2016: Physician investigators’ will start blinded reviews of potential medical errors and coding of content of transcribed work rounds.

June 7, 2016 End of data collection. Completion of last randomized 2 week block


28

H. Primary Qualifications of Research Team

Principal Investigator:

Dr. Kathleen Finn is an Assistant Professor of Medicine at Harvard Medical School and the

Inpatient Associate Program Director for Internal Medicine at Massachusetts General Hospital.

She is actively involved in the training and evaluation of medical residents. She was the PI for a

$100,000 Partners Reengineering Grant and led a team evaluating discharge facilitators

embedded in resident teams. The study was published in the Journal of Hospital Medicine. She

has also led several quality improvement projects and is actively involved in residency

education redesign.

Research Team:

Dr. Christiana Iyasere is an Instructor at Harvard Medical School and a member of the Inpatient

Clinician Educator Service at Massachusetts General Hospital. She is actively involved in the

training and evaluation of medical residents in addition to development of novel curricula in

medical leadership. Dr. Iyasere attended Columbia Medical School and Harvard Business

School. She has been actively involved in research projects looking at novel ways to promote

ongoing clinical mentorship of junior hospitalists, and the role of discharge facilitators on

resident teams. She will be co‐lead investigator in this project.

Dr. Joshua Metlay is Professor of Medicine at Harvard Medical School and Chief of the Division

of General Internal Medicine at Massachusetts General Hospital. He has led numerous multi‐

institutional clinical studies, including cluster randomized trials, and has specific expertise in

developing methods for primary and secondary data collection, outcome measurement and

analysis. He has also led several training programs, including serving as the PI of two federally

funded institutional Career Development studies. He is serving as lead advisor.

Dr. Hasan Bazari is Associate Professor of Medicine at Harvard Medical School and the Emeritus

Residency Program Director for Internal Medicine at Massachusetts General Hospital. He has

participated in numerous research projects evaluating resident education, work structure and

sleep deprivation and well being. He is serving as one of the physician Investigator to the

project.


29

Dr. Jatin M. Vyas is Associate Professor of Medicine at Harvard Medical School and the

Residency Program Director for Internal Medicine at Massachusetts General Hospital. He is an

NIH‐funded investigator in the area of fungal immunology. He served as the Chief Resident in

Medicine after training and actively participates in resident education and direct observation of

housestaff for over 15 years. He is serving as one of the physician investigators.

Dr. Yuchiao Chang is Assistant Professor of Medicine at Harvard Medical School and Statistician

at Massachusetts General Hospital. She is currently supporting all research activities for

Emergency Department and the Division of General Internal Medicine at Massachusetts

General Hospital. Dr. Chang has been the principal statistician for more than 50

federally/industrially funded grants, including cluster randomized trials. She has extensive

experience with various types of clinical data and advanced statistical methodology as reflected

by her list of more than 250 publications. She will be the primary statistician.

Dr. Elyse Park is Associate Professor of Psychiatry at Harvard Medical School and Director of

Behavioral Health Research at the Benson‐Henry Institute for Mind Body Medicine at

Massachusetts General Hospital. Dr. Park is an expert if mix‐methods approach and qualitative

research. She has been on numerous grants and studies involving qualitative research around

smoking cessation, palliative care and relaxation response. She will be serving as advisor and

statistician for the qualitative component of this study.


30

I. Biographical Data Form

BIOGRAPHICAL DATA FORM

1. Name/Position in Project: Kathleen Finn Principal Investigator 2. Education/Training:

Institution and Location Degree Year(s) Field of Study

University of Pennsylvania BA 1987 Anthropology

Oxford University M.Phil 1989 Social Anthropology

Bryn Mawr College 1990 Post‐Baccalaureate

Harvard Medical School M.D. 1995 Medicine

3. Research and Professional Experience: 1998‐2009 Instructor in Medicine Harvard Medical School 2004‐2006 Medical Director of the General Medical Service Brigham & Women’s Hosp 2008‐present Inpatient Associate Program Director, MGH Internal Medicine Residency Program Department of Medicine 2008‐present Director of MGH Annual Teaching Retreat MGH 2008‐2009 Principal Investigator Partners Physician Education Care Delivery Reengineering Innovation Grant. 2009 Harvard MACY program Educators in Health Professions 2009 Physician Leadership Development Certificate Program – MGPO MGH 2009 – present Assistant and Associate Editor Journal of Hospital Medicine 2010 Assistant Professor of Medicine Harvard Medical School 2012 Kranes Award for Excellence in Clinical Teaching MGH 2014 Charles Burnett Special Recognition Award MGH 2014 ACP Top Hospitalist’s for 2014

4. Publications: 1. Finn K, Heffner R, Chang Y, Bazari H, Hunt D, Pickell K, Berube R, Raju S, Farrell E, Iyasere

C, Thompson R, O’Malley T, O’Donnell W and Karson A. Improving the Discharge Process by

Embedding a Discharge Facilitator in a Resident Team. J Hosp Med 2011; 6(9):494‐500.


31

2. Finn K, Chiappa V, Puig A, and Hunt DP. How to become a better clinical teacher: a collaborative peer observation process. Med Teach 2011; 33(2):151‐155.

3. Finn K and Greenwald J. Hospitalists and Alcohol Withdrawal: Yes Give Benzodiazepines, but is that the Whole Story? J Hosp Med. 6(8):435‐7, 2011 Oct 6. 4. Finn, K. Inpatient Management of Alcohol Withdrawal. Hospital Medicine Clinics. Volume 1, Issue 1, pages A1‐A10, e132‐147 (January 2012). 5. Finn, K and Hunt, D. Editors. Hospital Medicine Clinics. Volume 1, Issue 4, Pages A1‐A10, e427‐e558 (October 2012) 6. Soverow J, McGarrah R, Editors. Finn, K, Wright D and Puig A Co‐Editors. The Evidence: Classic and influential studies every medicine resident should know. Selected Nights, LLC. 2013. 7. Dankers, C and Finn, K. Non‐Invasive Mechanical Ventilation. In: Decision Support in Medicine, Hospital Medicine. Decision Support in Medicine, LLC. 2013 8. Journal Watch. Hospital Medicine/Pediatrics and Adolescent Medicine. August 19, 2013. The Check‐Out Checklist. Finn, KM and Dressler D, reviewing Soong C et al. J Hosp Med 2013 Aug. 9. Journal Watch. Hospital Medicine/Cardiology. Sept 9, 2013. Drug Safety: All Statins are Not Created Equal. Finn, KM and Dressler D, reviewing Naci H et al. Circ Cardiovasc Qual Outcomes 2013 Jul. 10. Ramani S, Finn K, Katz JT, Yialamas M. Beyond Show and Tell: Promoting physical examination skills as essential habits of reflective practice. Academic Internal Medicine Insight. 2014;12(1):7‐8,13.

11. Shoeb, M, Khanna R, Fang M, Sharpe B, Finn K, Ranji, S and Monash B. Internal Medicine Rounding Practices and the ACGME Core Competencies. J Hosp Med 2014; 9(4):239‐243.

12. Finn KM, Ginns CL, Robbins GK, Wu CC, Branda JA. Case records of the Massachusetts General Hospital. Case 20‐2014. A 65‐year‐old‐man with dyspnea and progressively worsening lung disease. NEJM. 370(26):2521‐30.


32


Name/Position in Project: Christiana Iyasere, Co‐Lead Investigator Education/Training: Institution and Location Degree Year(s) Field of Study

Columbia University, College of Physicians and Surgeons MD 2002 Medicine

Harvard Business School MBA 2008 Business

Research and Professional Experience: Instructor in Medicine, Harvard Medical School 2006‐current

Clinician Educator Service, Massachusetts General Hospital 2008‐current

Associate Director, MGH Innovation Support Center 2008‐current

Publications: Christiana A. Iyasere, M.D., Leigh H. Simmons, M.D., Florian J. Fintelmann, M.D., and Anand S.

Dighe, M.D. Case 38‐2014 – An 87 Year‐Old Man with Sore Throat, Hoarseness, Fatigue and

Dyspnea. N Engl J Med 2014; 371:2321‐2327December 11, 2014.


33


Name/Position in Project: Joshua Metlay Senior Advisor – Physician Investigator

Education/Training: Institution and Location Degree Year(s) Field of Study

Yale University, New Haven, CT B.A. 05/84 Biology Rockefeller University, New York, NY Ph.D. 06/90 Immunology Cornell University, New York, NY M.D. 05/91 Medicine

Harvard School of Public Health, Boston, MA M.Sc. 06/97 Health Policy/Management

Research and Professional Experience: 1995‐97 Clinical and Research Fellow in Medicine, Massachusetts General Hospital, Boston

1997‐2006 Assistant Professor of Medicine and Epidemiology, University of Pennsylvania

1997‐2013 Senior Scholar, Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania

1997‐2009 Staff Physician, Veterans Affairs Medical Center, Philadelphia, PA 1997‐2013 Senior Fellow, Leonard Davis Institute of Health Economics,University of Penn

2006‐2010 Associate Professor of Medicine and Epidemiology (Tenure), University of Penn

2006‐2010 Program Leader, Doris Duke Clinical Research Fellowship, University of Penn

2006‐2013 Co‐Director, Robert Wood Johnson Foundation Clinical Scholars Program

University of Pennsylvania School of Medicine

2009‐2013 Chief, Section of Hospital Medicine, University of Pennsylvania School of Med

2009‐2013 Director, Center for Healthcare Improvement and Patient Safety,

University of Pennsylvania School of Medicine

2010‐2013 Professor of Medicine, Emergency Medicine and Epidemiology, University of

Pennsylvania

2013‐ Chief, Division of General Medicine, Massachusetts General Hospital, Boston

2013‐ Professor of Medicine, Harvard Medical School

Honors


34

1982 Phi Beta Kappa, Yale University

1989 Alpha Omega Alpha, Cornell University Medical College

1995 National Associates Award for Outstanding Research, Society of General Internal

Medicine

1999 Robert Wood Johnson Foundation Generalist Physician Faculty Scholar

2003 Robert Austrian Faculty Research Award. Department of Medicine. University of

Pennsylvania

2005 Penn Pearls Teaching Award, University of Pennsylvania School of Medicine

2008 Christian and Mary Lindback Foundation Award for Distinguished Teaching

2009 Samuel Martin Health Evaluation Sciences Research Award, University of Penn

2010 Mid‐Career Research and Mentorship Award, Society of General Internal Med

2011 Arthur Asbury Outstanding Faculty Mentor Award, University of Pennsylvania

2012 American Epidemiological Society

2014 Award for Excellence in Research, Society of Hospital Medicine

Publications:

1. Metlay JP, Lautenbach E, Li Y, Shults J, Edelstein PH: The changing role of exposure to children as a risk factor for bacteremic pneumococcal disease in the post conjugate vaccine era. Archives of Internal Medicine. 2010;170:725‐731. NIHMS 15969

2. Soneji S, Metlay J. Mortality reductions for older adults differ by race/ethnicity and gender since the introduction of adult and pediatric pneumococcal vaccines. Public Health Reports. 2011;126:259‐269. PMCID: PMC3056039

3. Feemster KA, Li Y, Localio AR, Shults J, Edelstein P, Lautenbach E, Smith T, Metlay JP: Risk of invasive pneumococcal disease varies by neighborhood characteristics: Implications for prevention policies. Epidemiology and InfectionEpub ahead of print Oct, 2012. PMCID: PMC Journal‐In Process.

4. Gonzales R, Anderer T, McCulloch CE, Maselli JH, Bloom FJ, Graf TR, Stahl M, Yefko M, Molecavage J, Metlay JP: A cluster‐randomized trial of decision support strategies for reducing antibiotic use for acute bronchitis. JAMA Internal Medicine. 173:267‐273, 2013.PMCID:PMC3582762


35


Name/Position in Project: Hasan Bazari Physician Investor

Education/Training: Institution and Location Degree Year(s) Field of Study

1976 B.A Biology Columbia College, New York

1978 M.A. Biology Columbia University New York

1979 M.Ph Biology( Dr.Cyrus Levinthal) Columbia University, New York

1983 M.D. Medicine Albert Einstein College of Medicine, New York.

Research and Professional Experience: Program Director emeritus

Director, Swartz Initiative

Associate Professor of Medicine

2010 Winner of the Alfred Krane Award

2011 Honor Roll for the Partners Program Director Award

2011 Principal Clinical Experience Teaching Award

2011 Gold Humanism Award

2012 Excellence in Clinical Teaching


36

2013 Outstanding Program Director Award

Publications: a.Ripp J, Babyatsky M, Fallar R, Bazari H, Bellini L, Kapadia C, Katz J, Pecker M, Korenstein D. The

incidence and predictors of job burnout in first‐year residents: A five institution study.

Academic Medicine 2011;86:1304‐1310.

b. Finn K, Heffner R, Chang Y, Bazari H, Hunt D, Pickell K, Berube R, Raju S, Farrell E, Iyasere C,

Thompson R, O’Malley T, O’Donnell W and Karson A. Improving the Discharge Process by

Embedding a Discharge Facilitator in a Resident Team. Jour of Hospital Medicine 2011:6:494‐

500

c.Caverzagie KJ, Iobst WF, Aagard EM, Hood S, Chick DA, Kane GC, Brigham TP, Swing SR, Meade

LB, Bazari H, Bush RW, Kirk LM, Green ML, Hinchey KT and Smith,CD. The Internal Medicine

Reporting Milestones and the Next Accreditation System. Annals of Internal Medicine

2013;158:557‐9.

d.. Leaf DE, Pereira RC, Bazari H, Juppner H. Oncogenic Osteomalacia due to FGF‐23 Expressing

Colon Adenocarcinoma. The Journal of Clinical Endocrinology and Metabolism 2013

Mar;98(3):887‐91.

e..Intravenous moderate‐dose bumetanide continuous infusion and severe musculoskeletal

pain Vaduganathan M, Allegretti AS, Manchette AM, Patel SS, Olson KR, Bazari, H. Int J Cardiol

2013 Sept 20:168(1):e29‐31.


37


Name/Position in Project: Jatin M. Vyas, MD, PhD ‐ Residency Program Director Physician Investigator Education/Training: Institution and Location Degree Year(s) Field of Study

University of Texas at Austin B.A. (plan II) 1985‐1989 Liberal Arts Honors Program

Baylor College of Medicine Ph.D. 1989‐1994 Microbiology and Immunology

Baylor College of Medicine M.D. 1989‐1996 Medicine

Research and Professional Experience: 2007‐present Faculty, Division of Infectious Disease, Department of Medicine, Massachusetts

General Hospital, Harvard Medical School

2011‐present PI on 2 NIH R01 to fund basic investigations in the Innate Immune Responses to

Fungal Pathogens

2014‐present Residency Program Director for the Department of Medicine, Massachusetts

General Hospital

Publications:

1. Tam JM, Mansour MK, Khan NS, Yoder NC, Vyas JM. Use of fungal derived polysaccharide‐

conjugated particles to probe Dectin‐1 responses in innate immunity. 2012. Integrative Biology

(Camb). Feb 1;4(2) 220‐7.

2. Huett A, Heath RJ, Begun J, Sassi SO, Baxt LA, Vyas JM, Goldberg MB, Xavier RJ. The LRR‐ and RING‐

domain protein LRSAM1 is an E3 ubiquitin ligase crucial for ubiquitin‐dependent autophagy of

intracellular Salmonella typhimurium. 2012 Cell: Host and Microbe. Dec 13;12(6):778‐90

3. Vyas, JM, Marasco WA. Fatal Fulminant Hepatic Failure from Adenovirus in Allogeneic Bone Marrow Transplant Patients. Case Reports in Infectious Disease. 2012.2012:463569.

4. Bell T. Vyas, JM. Prosthetic Joint Infections. Hospital Medicine Clinics. 2012. 1 e498‐e507.

5. Mansour MK, Tam JM, Vyas JM. The Cell Biology of the Innate Immune Response to Aspergillus fumigatus. Annals of the New York Academy of Sciences. 2012. Dec;1273(1):78‐84.


38

6. Vyas JM. The Dendritic Cell: The General of the Army. Virulence. 2012. Nov 15;3(7):601‐602.

7. Vyas JM. Insights into Dendritic Cell Function Using Advanced Imaging Modalities. Virulence. 2012. Nov 15;3(7): 690‐694.

8. Grimm, MJ, Vethanayagam RR, Almyroudis NG, Dennis CG, Khan ANH, D’Auria1 A, Singel KL,

Davidson BA, Knight PR, Blackwell TS, Hohl TM, Mansour MK, Vyas JM, Röhm M, Urban CF, Kelkka T,

Holmdahl R, Segal BH. Monocyte and macrophage‐targeted NADPH oxidase mediates antifungal host

defense and regulation of acute inflammation in mice. 2013. The Journal of Immunology. Apr

15;190(8):4175‐84.

9. Mansour MK, Tam JM, Khan NS, Seward M, Davids PJ, Puranam S, Sokolovska A, Sykes DB, Dagher Z,

Becker C, Tanne A, Reedy JL, Stuart LM, and Vyas JM. Dectin‐1 activation controls maturation of β‐1,3‐

glucan‐containing phagosomes. 2013. Journal of Biological Chemistry. Apr 22. 288(22):16043‐54

10. Vyas JM, González RG, Pierce VM. Case records of the Massachusetts General Hospital. A 76‐Year‐Old Man with Fever, Worsening Renal Function, and Altered Mental Status. New England Journal of Medicine. 2013. May 16;368(20):1919‐27.

11. Kasper L, Seider K, Gerwien F, Allert S, Brunke S, Schwarzmüller T, Ames L, Barrera CZ, Mansour MK, Becken U, Barz D, Vyas JM, Reiling N, Haas A, Haynes K, Kuchler K and Hube B. Identification of Candida glabrata genes involved in pH modulation and modification of the phagosomal environment in macrophages. 2014. PloS One. May 1;9(5):e96015.

12. Tam JM, Mansour MK, Khan NS, Seward M, Puranam S, Tanne A, Sokolovska A, Becker CE, Acharya

M, Baird MA, Choi AMK, Davidson MW, Segal BH, Lacy‐Hulbert A, Stuart LM, Xavier RJ, and Vyas JM.

Dectin‐1‐Dependent LC3 Recruitment to Phagosomes Enhances Fungicidal Activity in Macrophages.

2014. The Journal of Infectious Disease. Dec 1;210(11):1844‐54.

13. Klassert TE, Hanisch A, Bräuer J, Klaile E, Heyl KA, Mansour MM, Tam JM, Vyas JM, Slevogt H.

Modulatory role of vitamin A on the Candida albicans‐induced immune response in human monocytes.

2014. Medical Microbiology and Immunology. Dec;203(6):415‐24

14. Mansour MK, Reedy JL, Tam JM and Vyas JM. Macrophage‐Cryptococcus Interactions: An Update.

2014. Current Fungal Infections Report. Mar 1;8(1):109‐115.


39


Name/Position in Project: Yuchiao Chang, Statistician

Education/Training:


National Taiwan University, Taipei, Taiwan BS 06/86 Agronomy

Yale University, New Haven, Connecticut MA 05/89 Statistics

Carnegie Mellon University, Pittsburgh, PA PhD 12/93 Statistics

Research and Professional Experience:

Positions:

1986‐1987 Research Assistant, Biometry Laboratory, National Taiwan University 1991‐1992 Summer Lecturer, Department of Statistics, Carnegie Mellon University 1989‐1993 Teaching Assistant, Department of Statistics, Carnegie Mellon University 1998‐2001 Statistical Consultant, Gastroenterology 1993‐2005 Instructor in Medicine, Department of Medicine, Harvard Medical School 1993‐2006 Assistant Biostatistician, Massachusetts General Hospital, Boston, MA 1998‐2007 Statistical Consultant, Journal of Clinical Anesthesia 2005‐current Assistant Professor in Medicine, Department of Medicine, Harvard Medical

School 2006‐2012 Associate Biostatistician, Massachusetts General Hospital, Boston, MA 2012‐current Biostatistician, Massachusetts General Hospital, Boston, MA Honors: 1993 Biometric Society Student Award 1995 American Cancer Society Institutional Research Grant Award Publications:

Winickoff JP, Nabi‐Burza E, Chang Y, Finch S, Regan S, Wasserman R, Ossip D, Woo H, Klein J,

Dempsey J, Drehmer J, Hipple B, Weiley V, Murphy S, Rigotti NA. Implementation of a

Parental Tobacco Control Intervention in Pediatric Practice. Pediatrics. 2013 Jun 24. [Epub

ahead of print] PubMed PMID: 23796741; PubMed Central PMCID: PMC3691536.

Kruse GR, Chang Y, Kelley JH, Linder JA, Einbinder JS, Rigotti NA. Healthcare system effects of

pay‐for‐performance for smoking status documentation. Am J Manag Care. 2013

Jul;19(7):554‐61. PubMed PMID: 23919419.

Rodriguez F, Hong C, Chang Y, Oertel LB, Singer DE, Green AR, López L. Limited english

proficient patients and time spent in therapeutic range in a warfarin anticoagulation clinic. J


40

Am Heart Assoc. 2013 Jul 5;2(4):e000170. doi: 10.1161/JAHA.113.000170. PubMed PMID:

23832325.

Mejaddam AY, Elmer J, Sideris AC, Chang Y, Petrovick L, Alam HB, Fagenholz PJ. Prolonged

Emergency Department Length of Stay is Not Associated with Worse Outcomes in Traumatic

Brain Injury. J Emerg Med. 2013 Jun 12. doi:pii: S0736‐4679(13)00452‐6.

10.1016/j.jemermed.2013.04.015. [Epub ahead of print] PubMed PMID: 23769388.

Lobachova L, Brown DF, Sinclair J, Chang Y, Thielker KZ, Nagurney JT. Patient and Provider

Perceptions of Why Patients Seek Care in Emergency Departments. J Emerg Med. 2013 Sep

21. doi:pii: S0736‐4679(13)00830‐5. 10.1016/j.jemermed.2013.04.063. [Epub ahead of print]

PubMed PMID: 24063881.

Brouwers HB, Chang Y, Falcone GJ, Cai X, Ayres AM, Battey TW, Vashkevich A, McNamara KA,

Valant V, Schwab K, Orzell SC, Bresette LM, Feske SK, Rost NS, Romero JM, Viswanathan A,

Chou SH, Greenberg SM, Rosand J, Goldstein JN. Predicting Hematoma Expansion After

Primary Intracerebral Hemorrhage. JAMA Neurol. 2013 Dec 23. doi:

10.1001/jamaneurol.2013.5433. [Epub ahead of print] PubMed PMID: 24366060.

Sepucha K, Feibelmann S, Chang Y, Hewitt S, Ziogas A. Measuring the quality of surgical

decisions for Latina breast cancer patients. Health Expect. 2014 May 12. doi:

10.1111/hex.12207. [Epub ahead of print] PubMed PMID: 24813584.

Rigotti NA, Regan S, Levy DE, Japuntich S, Chang Y, Park ER, Viana JC, Kelley JH, Reyen M,

Singer DE. Sustained care intervention and postdischarge smoking cessation among

hospitalized adults: a randomized clinical trial. JAMA. 2014 Aug 20;312(7):719‐28. doi:

10.1001/jama.2014.9237. PubMed PMID: 25138333.

Kimo Takayesu J, Ramoska EA, Clark TR, Hansoti B, Dougherty J, Freeman W, Weaver KR,

Chang Y, Gross E. Factors Associated With Burnout During Emergency Medicine

Residency. Acad Emerg Med. 2014 Sep;21(9):1031‐1035. doi: 10.1111/acem.12464. PubMed

PMID: 25269584.

White BA, Chang Y, Grabowski BG, Brown DF. Using lean‐based systems engineering to

increase capacity in the emergency department. West J Emerg Med. 2014 Nov;15(7):770‐6.

doi: 10.5811/westjem.2014.8.21272. Epub 2014 Oct 10. PubMed PMID: 25493117; PubMed

Central PMCID: PMC4251218.

Baggett TP, Chang Y, Singer DE, Porneala BC, Gaeta JM, O'Connell JJ, Rigotti NA. Tobacco‐,

Alcohol‐, and Drug‐Attributable Deaths and Their Contribution to Mortality Disparities in a

Cohort of Homeless Adults in Boston. Am J Public Health. 2014 Dec 18:e1‐e9. [Epub ahead of

print] PubMed PMID: 25521869.


41


Name/Position in Project: Elyse R. Park Qualitative Researcher

Education/Training:


Tufts University, Medford, MA B.A. 1988 Social Psychology Yeshiva University, Bronx, NY Ph.D. 1997 Clinical Health

Harvard School of Public Health, Boston, MA MPH 2007 Behavioral Medicine Public Health

Research and Professional Experience:

1990‐1991 Research Intern, Memorial Sloan Kettering Cancer Center, New York, NY.

1993‐1995 Graduate Research Assistant, Albert Einstein College of Medicine, Bronx, 1995‐1996 Psychology Intern, APA approved Clinical Psychology/Behavioral Medicine

Program. Union Memorial Hospital, Baltimore, MD. 1996‐1998 Behavioral Medicine Fellow. Brown Medical School, Providence, RI. 1998‐2000 Research Associate, Dana‐Farber Cancer Institute, Boston, MA. 2001‐2006 Instructor, Department of Psychiatry, Harvard Medical School, Boston, M.

2006‐2011 Assistant Professor, Department of Psychiatry, Harvard Medical School, B 2007‐2010 Chief of Behavioral Health Research, Benson‐Henry Institute for Mind 2009‐ Director of Behavioral Sciences, MGH Center for Psychiatric Oncology and

Behavioral Sciences at the Cancer Center 2009‐ Director of Behavioral Science Research, MGH Tobacco Research & Treatment Center

2010‐ Director of Behavioral Health Research, Benson‐Henry Institute for Mind Body Med 2011‐ Associate Professor, Department of Psychiatry, Harvard Medical School

Honors

1991‐1994 Academic Scholarship (Yeshiva University, Bronx, NY)

1993‐1994 Jewish Foundation for Education of Women Award

2005 Author of top 25 most read articles of 2005 (Health Affairs)

2006 Behavioral Medicine Excellence in Mentorship Award (MGH, Boston, MA)

2008 4th Biennial Survivorship Research Conference Meritorious Presentation

2010 Clinical Innovator Award, MGH Cancer Center’s Psychiatric Oncology and

Behavioral Sciences Center

2014 Mentor: Best poster, 11th annual American Psychosocial Oncology Society

5. Publications: Mueller E, Park ER, Davis M. What the Affordable Care Act Means for Survivors of Pediatric Cancer. Journal of Clinical Oncology. 2014; 32:615‐7.


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El‐Jawahri A, Traeger L, Park ER, Greer JA, Pirl WF, Lennes IT, Jackson VA, Gallagher ER, Temel JS.Associations among prognostic understanding, quality of life, and mood in patients with advanced cancer. Cancer. 2014; 15: 278‐285. Kirchhoff AC, Montenegro RE, Warner EL, Wright J, Fluchel M, Stroup AM, Park ER, Kinney AY. Support Care Cancer. Childhood cancer survivors' primary care and follow‐up experiences. 2014; 22: 1629‐35. Traeger L, Cannon S, Keating NL, Pirl WF, Lathan C, Martin MY, He Y, Park ER. Race by sex differences in depression symptoms and psychosocial service use among non‐Hispanic black and white patients with lung cancer. J Clin Oncol. 2014; 32(2):107‐13. Gareen I, Duan F, Greco EM, Snyder BS, Boiselle PM, Park ER, Fryback D, Gatsonis C. Impact of Lung Cancer Screening Results On Participant Health‐Related Quality Of Life and State anxiety in the National Lung Screening Trial. Cancer. 2014. 120: 3401‐9. Vranceanu A, Gonzalez A, Denninger J, Baim P, Park ER. Exploring the effectiveness of a modified comprehensive mind‐body intervention for medical and psychological symptom relief. Psychosomatics. 2014; 55:386‐91. Gonzalez A., Keating N, Japuntich S, He L, Wallace R, Park ER. Pain Experiences among a Population‐Based Cohort of Current, Former and Never Regular Smokers with Lung and Colorectal Cancer. Cancer 2014; 120:3554‐61. Back AL, Park ER, Greer J, Jackson V, Temel JS. Clinician roles in early integrated palliative care for patients with advanced cancer: a qualitative study. Journal of Palliative Medicine. 2014; 17:1244‐8. Rigotti NA, Regan S, Levy DE, Japuntich S, Chang Y, Park ER, Viana JC, Kelley JH, Reyen M, Singer DE. Sustained care intervention and post‐discharge smoking cessation among hospitalized adults: a randomized clinical trial. JAMA. 2014; 312:719‐28. Vranceanu AM Merker VL, Plotkin SR, Park ER. The Relaxation Response Resiliency Program (3RP) in patients with NF1, NF2, and schwannomatosis: Results from a pilot study. Journal of Neurooncology 2014; 120:103‐9. Huffman J., Moore S., DuBois C., Mastromauro C., Suarez L. & Park ER. An exploratory mixed methods analysis of adherence predictors following acute coronary syndrome. Psychology, Health, and Medicine. 2014; 15: 1‐10.


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J. Appendices

References – Literature Cited

1. Kennedy, T.J., et al., Progressive independence in clinical training: a tradition worth defending? Acad Med, 2005. 80(10 Suppl): p. S106‐11.

2. Kennedy, T.J., et al., Clinical oversight: conceptualizing the relationship between supervision and safety. J Gen Intern Med, 2007. 22(8): p. 1080‐5.

3. Halpern, S.D. and A.S. Detsky, Graded autonomy in medical education‐‐managing things that go bump in the night. N Engl J Med, 2014. 370(12): p. 1086‐9.

4. Kennedy, T.J., Towards a tighter link between supervision and trainee ability. Med Educ, 2009. 43(12): p. 1126‐8.

5. Bell, B.M., Resident duty hour reform and mortality in hospitalized patients. JAMA, 2007. 298(24): p. 2865‐6; author reply 2866‐7.

6. Farnan, J.M., et al., Strategies for effective on‐call supervision for internal medicine residents: the superb/safety model. J Grad Med Educ, 2010. 2(1): p. 46‐52.

7. Volpp, K.G., et al., Mortality among hospitalized Medicare beneficiaries in the first 2 years following ACGME resident duty hour reform. JAMA, 2007. 298(9): p. 975‐83.

8. Desai, S.V., et al., Effect of the 2011 vs 2003 duty hour regulation‐compliant models on sleep duration, trainee education, and continuity of patient care among internal medicine house staff: a randomized trial. JAMA Intern Med, 2013. 173(8): p. 649‐55.

9. Sen, S., et al., Effects of the 2011 duty hour reforms on interns and their patients: a prospective longitudinal cohort study. JAMA Intern Med, 2013. 173(8): p. 657‐62; discussion 663.

10. Sox, C.M., et al., The effect of supervision of residents on quality of care in five university‐affiliated emergency departments. Acad Med, 1998. 73(7): p. 776‐82.

11. Velmahos, G.C., et al., Around‐the‐clock attending radiology coverage is essential to avoid mistakes in the care of trauma patients. Am Surg, 2001. 67(12): p. 1175‐7.

12. Schmidt, U.H., et al., Effects of supervision by attending anesthesiologists on complications of emergency tracheal intubation. Anesthesiology, 2008. 109(6): p. 973‐7.

13. Gennis, V.M. and M.A. Gennis, Supervision in the outpatient clinic: effects on teaching and patient care. Journal of general internal medicine, 1993. 8(7): p. 378‐80.

14. Baldwin, D.C., Jr., S.R. Daugherty, and P.M. Ryan, How residents view their clinical supervision: a reanalysis of classic national survey data. J Grad Med Educ, 2010. 2(1): p. 37‐45.

15. Phy, M.P., et al., Increased faculty presence on inpatient teaching services. Mayo Clin Proc, 2004. 79(3): p. 332‐6.

16. Defilippis, A.P., et al., On‐site Night Float by Attending Physicians: A Model to Improve Resident Education and Patient Care. J Grad Med Educ, 2010. 2(1): p. 57‐61.

17. Trowbridge, R.L., et al., The effect of overnight in‐house attending coverage on perceptions of care and education on a general medical service. J Grad Med Educ, 2010. 2(1): p. 53‐6.

18. Landrigan, C.P., et al., Effect of a pediatric hospitalist system on housestaff education and experience. Arch Pediatr Adolesc Med, 2002. 156(9): p. 877‐83.


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19. Questions, A.D.H.R.F.A. Duty Hours Requirements: Frequently Asked Questions. 2011 2015]; Available from: https://www.acgme.org/acgmeweb/Portals/0/PDFs/dh‐faqs2011.pdf.

20. Kerlin, M.P., et al., A randomized trial of nighttime physician staffing in an intensive care unit. N Engl J Med, 2013. 368(23): p. 2201‐9.

21. Garland, A., D. Roberts, and L. Graff, Twenty‐four‐hour intensivist presence: a pilot study of effects on intensive care unit patients, families, doctors, and nurses. Am J Respir Crit Care Med, 2012. 185(7): p. 738‐43.

22. Kilminster, S.M. and B.C. Jolly, Effective supervision in clinical practice settings: a literature review. Medical education, 2000. 34(10): p. 827‐40.

23. Lingard, L., et al., A certain art of uncertainty: case presentation and the development of professional identity. Social science & medicine, 2003. 56(3): p. 603‐16.

24. Starmer, A.J., et al., Rates of medical errors and preventable adverse events among hospitalized children following implementation of a resident handoff bundle. JAMA, 2013. 310(21): p. 2262‐70.

25. Starmer, A.J., et al., Changes in medical errors after implementation of a handoff program. The New England journal of medicine, 2014. 371(19): p. 1803‐12.

26. Kaushal, R., et al., Medication errors and adverse drug events in pediatric inpatients. JAMA, 2001. 285(16): p. 2114‐20.

27. Young, J.Q., et al., "July effect": impact of the academic year‐end changeover on patient outcomes: a systematic review. Annals of internal medicine, 2011. 155(5): p. 309‐15.

28. website, N.C.C.f.M.E.R.a.P. [cited January 9, 2015; Available from: http://www.nccmerp.org/types‐medication‐errors.

29. Goldszmidt, M., N. Aziz, and L. Lingard, Taking a detour: positive and negative effects of supervisors' interruptions during admission case review discussions. Academic medicine : journal of the Association of American Medical Colleges, 2012. 87(10): p. 1382‐8.

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THE EDWARD J. STEMMLER MD€¦ · mentorship, what constitutes “supervision” is not clearly defined. Resident oversight by attending physicians on the general inpatient medical