exemplary professional practice: staffing scheduling and ......exemplary professional practice:...

6
Exemplary Professional Practice: Staffing Scheduling and Budgeting Processes EP10 Nurses use trended data in the budgeting process, with clinical nurse input, to redistribute existing nursing resources or obtain additional nursing resources. EP10b: Provide an example, with supporting evidence, where trended data was used during the budget process, with clinical nurse input, to assess actual-to- budget performance to redistribute existing nursing resources or to acquire additional nursing resources. Trended data must be presented. Introduction As described in EP10a, the annual operational budget process provides a structure to acquire nurse staffing resources for the Massachusetts General Hospital (MGH) inpatient nursing units. Development of inpatient staffing budgets involves the use of trended data and assessment of actual to budget performance for a variety of metrics. Input from clinical nurses is used by nurse leaders and managers to inform decisions made during the budget process as well as at other points during the fiscal year when adjustments may need to be made to redistribute or acquire additional nursing resources based on increased nursing workload. MGH Inpatient Staffing Model with Staff Nurse Input At MGH, staffing budgets are developed at the unit or cost center level during the annual operational budget development process that usually occurs from March through July of each year. The process involves quantifying the expected work of a nursing unit/department which, in turn, assists in determining the required personnel. The Quadramed AcuityPlus™ Productivity, Benchmarking, and Outcomes System - Inpatient Methodology (Quadramed) is used to quantify the nursing care needs for the MGH inpatient units. The Quadramed acuity system, sometimes to referred to as the “patient classification system”, assures that clinical nurses provide input, through their daily electronic data entry, that results in a measurement of patients’ needs for nursing care (i.e. acuity). The acuity values and volume that results from the clinical nurse input are used to provide a measurement of nursing workload, which is a function of both census and acuity. This daily input which reflects patient care needs based on nursing assessment is invaluable in the determination of required nursing resources. Each day clinical nurses complete the patient classification tool, a factor evaluation tool comprised of 24 indicators that are known to impact nursing workload. The resulting “score” aggregates patients into one of six categories with assigned values that are used to quantify the needs for nursing care in a 24-hour period. Additional information is added by the clinical nurses for an additional 11 categories of care that also impact

Upload: others

Post on 13-Jan-2020

12 views

Category:

Documents


0 download

TRANSCRIPT

Exemplary Professional Practice: Staffing Scheduling and Budgeting Processes EP10 Nurses use trended data in the budgeting process, with clinical nurse input, to redistribute existing nursing resources or obtain additional nursing resources. EP10b: Provide an example, with supporting evidence, where trended data was used during the budget process, with clinical nurse input, to assess actual-to-budget performance to redistribute existing nursing resources or to acquire additional nursing resources. Trended data must be presented. Introduction As described in EP10a, the annual operational budget process provides a structure to acquire nurse staffing resources for the Massachusetts General Hospital (MGH) inpatient nursing units. Development of inpatient staffing budgets involves the use of trended data and assessment of actual to budget performance for a variety of metrics. Input from clinical nurses is used by nurse leaders and managers to inform decisions made during the budget process as well as at other points during the fiscal year when adjustments may need to be made to redistribute or acquire additional nursing resources based on increased nursing workload. MGH Inpatient Staffing Model with Staff Nurse Input At MGH, staffing budgets are developed at the unit or cost center level during the annual operational budget development process that usually occurs from March through July of each year. The process involves quantifying the expected work of a nursing unit/department which, in turn, assists in determining the required personnel. The Quadramed AcuityPlus™ Productivity, Benchmarking, and Outcomes System - Inpatient Methodology (Quadramed) is used to quantify the nursing care needs for the MGH inpatient units. The Quadramed acuity system, sometimes to referred to as the “patient classification system”, assures that clinical nurses provide input, through their daily electronic data entry, that results in a measurement of patients’ needs for nursing care (i.e. acuity). The acuity values and volume that results from the clinical nurse input are used to provide a measurement of nursing workload, which is a function of both census and acuity. This daily input which reflects patient care needs based on nursing assessment is invaluable in the determination of required nursing resources. Each day clinical nurses complete the patient classification tool, a factor evaluation tool comprised of 24 indicators that are known to impact nursing workload. The resulting “score” aggregates patients into one of six categories with assigned values that are used to quantify the needs for nursing care in a 24-hour period. Additional information is added by the clinical nurses for an additional 11 categories of care that also impact

nursing workload, such as a patient who must travel off the unit for a procedure with an RN or the need of 1:1 observation for safety reasons. Additional information is added from the hospital’s eCare system to capture nursing time related to admissions, discharges, and transfers. The resulting workload information then quantifies the staffing requirements, based on hours of care, for each patient and unit.

Since the Quadramed data is key to decision making related to acquiring or redistributing valuable nursing resources, there is a strong focus on daily compliance with the data entry requirements and the reliable use of the tool. All clinical nurses receive education regarding patient classification during their central onboarding, which is reinforced during their unit-based orientation with an RN preceptor. The rate of completed classification events is monitored and consistently demonstrates a compliance rate of approximately 98%. In addition, inter-rater reliability is audited on an on-going basis to assure reliable application of the tool and the consistent interpretation of indicators.

These efforts based on input from clinical nurses result in quantification of nursing workload that can be used in the budgeting for the nurse staffing resources required to meet the workload demands. Nursing & Patient Care Services Management Systems & Financial Performance (N&PCS MSFP) supports nursing leadership during this annual budget process, and throughout the year by monitoring actual-to-budget performance of workload and productivity.

Utilization of Trended Data During the Budget Process

The MGH Budget Office begins the process by providing trended data for volume statistics to be used in developing the next year’s high-level budget assumptions. Data specific to admissions and discharges, length of stay, and patient days are provided for each service to demonstrate trends and patterns in patient volume. Together with information about internal and external factors affecting the organization, this data is used to forecast overall volume for the next fiscal year. Attachment EP10b.a contains the volume trends that were presented and used in the Fiscal Year 2018 (FY’18) budget development process, which shows that the proposed volume would have a 5.9 % decrease in discharges, a slight decrease in LOS, and an overall decrease in patient days and projected Average Daily Census (ADC) of 4.1% over FY’17. A year-to-date (YTD) trend report of the actual census by clinical service by unit is then used to establish the expected ADC for each unit for the coming year.

The N&PCS MSFP compiled YTD unit-level data from Quadramed for LOS Adjusted Census, Average Acuity, Hours Per Workload Index, Direct Care Shifts used per 24 Hours, and actual RN versus Non-RN Skill Mix. YTD data was analyzed to determine the difference between the Midnight ADC and LOS Adjusted Census for each unit. The trend for average acuity from October 2016 through February 2017 was also analyzed and then used with the census data to quantify the expected need for nursing care or the unit’s workload. This workload or “Workload Index,” calculated as LOS Census X

Acuity, is quantified for each unit. The established staffing targets for Hours Per Workload Index (HPWI) were then applied to the workload to calculate the required direct care clinical nurse and patient care associate (i.e. unlicensed assistive personnel) Full Time Equivalents (FTEs).

To complete the FTE calculations for each inpatient unit, N&PCS MSFP created a summary of actual benefit time utilization based on the previous 12 months, so as to account for seasonal variations and trends. This percentage is added to the calculated direct care FTEs to assure backfill staffing to cover paid time off for direct care staff. For FY’18, an average of 14.1% for clinical nurses and 10.6% for patient care associates was added to the FTE budgets to cover expected time off. A percentage of 4.4% was then added to cover the indirect time needed for orientation, education, professional development and administrative project time. Note that the indirect time addition was reduced from 4.5% as used in the FY’17 budget to 4.4% for the FY’18 budget to reflect a planned decrease in central onboarding time and a reduction of 2.3 FTEs in the indirect time budget for the inpatient units. The resulting data will provide the total FTEs for direct care staff to be included in the FY’18 budget for each unit. Trended acuity data from Quadramed and actual benefit time by role group that was compiled to form the basis for the FY’18 budget process are included as attachment EP10.b.b.

During the process, the Associate Chief Nurses provide feedback about the trended data and initial staffing calculations, including explanations of actual or expected variances. They advise the N&PCS MSFP staff as to whether or not the trended data is appropriate to use for staffing calculations. They also critically review the budget targets for RN mix and provide recommendations for desired changes. The Associate Chief Nurses share the results of the calculations using the trended data with the Nursing Directors (NDs) during the process, to obtain their “front-line” insight about the proposed changes.

For the FY’18 budget process, some of this planning and feedback occurred earlier in the year as a result of work with a consultant engaged by Partners Health Care who compared MGH actual staffing to national benchmarks for HPPD, as well as a review of internal staffing targets (HPWIs) for all Partners Hospitals. One proposal from this analysis was a decrease the internal staffing target (i.e. Hours Per Workload Index or HPWI) target by 0.05 for all units. The impact of this change was calculated and shared with the associate chief nurses who in turn communicated the proposal to the NDs in their areas. An example of this is contained in an e-mail from Theresa Gallivan, RN, MSN, NEA-BC, Associate Chief Nurse for Cardiac, Medicine and Emergency Nursing Services, on January 09, 2017 where she shared this proposal and asked for feedback from the NDs. Gallivan asked Chris Annese, RN, MSN, AHN-BC, Staff Specialist, to compile the feedback. In response, Judy Silva, RN, MSN, NE-BC, Nursing Director for the Cardiac Access Unit (Ellison 11) shared some concerns regarding the proposed reduction and its impact on her unit (attachment EP10b.c).

Assessment of Actual to Budget Performance

N&PCS MSFP produces weekly Workload/ Productivity Reports that provide an on-going tool for nursing leadership to monitor both workload and appropriate use of direct care staffing. The report provides an overview of actual to budget performance by unit, including weekly, month-to-date and year-to-date data. In her e-mail to Annese, Silva voiced her concerns and referenced her actual to budget performance in regards to nursing workload. She shared her concerns about the proposed reduction since Ellison 11 was performing “significantly above budget in workload.”

Although the census for Ellison 11 was running very close to the FY’17 budget target, the acuity and workload were running beyond the budget. The result was that the nursing staffing used per unit of workload (i.e. Hours Per Workload Index of HPWI) was falling short of the desired staffing target. Annese shared Silva’s concern with Nancy Raye, RN, MSN, Staff Specialist in N&PCS MSFP. Raye took the opportunity to clarify with Silva that, although the proposed reduction in Budget HPWI for FY’18 would ultimately result in slightly less staffing, that the changes she was seeing in acuity and workload would most likely result in additional staffing for Ellison 11. Raye provided this information in an e-mail response to Silva on January 10, 2017 (attachment EP10b.c) and discussed it further with her by phone. The feedback helped to frame the concerns regarding the actual to budget performance and, in advance of the formal budget submission, highlighted Ellison 11 as a unit expected to receive additional staffing for FY’18.

Shifts/24 Hours

Unit

Bud LOS

Census

Act LOS

Census

Bud Total

Acuity

Act Total

Acuity

Bud Total

WI

Act Total

WIBud

HPWIAct

HPWI

Bud Shifts

/24

Act Shifts

/24

Ellison 11 29.6 29.7 1.79 1.93 53.0 57.4 5.50 5.26 36.5 37.7

Shifts/24 Hours

Unit

Bud LOS

Census

Act LOS

Census

Bud Total

Acuity

Act Total

Acuity

Bud Total

WI

Act Total

WIBud

HPWIAct

HPWI

Bud Shifts

/24

Act Shifts

/24

Ellison 11 29.6 29.7 1.79 1.86 53.0 55.2 5.50 5.10 36.5 35.2

Census Acuity Workload HPWI

Census

Excerpt from Workload Productivity Report for the Week of January 7-14, 2017:

HPWIWorkloadAcuity

Excerpt from Workload Productivity Report for January 14, 2017 YTD:

Clinical Nurse Input Regarding Resource Distribution

NDs have a variety of ways that they communicate with clinical nurses on an on-going basis both to inform and receive feedback regarding the staffing budget. In addition to daily conversations with scheduled nursing staff, Silva holds unit-based staff meetings with all three shifts and then summarizes the discussions in an e-mail that she sends to all Ellison 11 clinical and advanced practice nurses. For example, at the September 9, 2016 staff meeting the Ellison 11 clinical nurses shared their opinions that since the EPIC go-live in the Spring of 2016, their experience had been that admissions were occurring later in the day and that there was additional workload during the 3PM – 7PM timeframe. This led to a discussion about how to staff the evening shift given the increasing workload. The staff provided open, honest feedback and proposed that they should minimize use of 12-hour evening shifts because the overlap from 11AM to 3PM was not necessary. They suggested using only 8-hour evening shifts, which would allow a move of the 11AM to 3PM hours to the evening (e.g. 3PM-11PM) timeframe where the increased workload was being experienced. Attachment EP10b.d contains the minutes distributed by Silva after the September 9, 2016 meeting where she thanks the nurses for their input regarding staffing.

Acquiring Additional Nursing Resources

To date, the initial submission for the FY’18 personnel budget has been completed and it is expected that due to the increased acuity and workload on Ellison 11, the unit’s direct care personnel budget will be increased for clinical nurses, by at least 1.4 FTEs. There is also an expected 1.9 FTE increase for Unlicensed Assistive Personnel. Further, as previously mentioned, Nurse Directors obtain input from clinical nurses throughout the year. Attachment EP10b.e contains the annual Budget Sheet that will be provided to Silva containing the information that was used in the budget process and the resulting changes in FTEs by role group.

In determining where to distribute these specific additional 3.3 FTEs of nursing resources, Silva will consider the input from the Ellison 11 clinical nurses that was provided at the September 2016 staff meeting. The translation of this clinical nurse input into the redistribution of resources is evidenced in the annual process MGH undergoes to report staffing plans through PatientCareLink. PatientCareLink, originally called Patients First, was created in 2005 and endorsed by the Massachusetts Hospital Association and the Massachusetts Organization of Nurse Executives (now the Organization of Nurse Leaders). As stated on the PatientCareLink website (www.PatientCareLink.org), the initiative is a healthcare quality and transparency collaborative supporting a “quality and safety initiative” that is “committed to the advancement of professional nursing, promoting the delivery of quality patient care and influencing the development of health policy.” All acute care hospitals participate in PatientCareLink and are required to post budgeted staffing plans on the Massachusetts Hospital Association website, presented by role group, day of the week, and shift. Nursing Directors review and approve this information on an annual basis. The table

below indicates how Silva will change the information for FY’18 to include the additional 3.3 FTEs, incorporating the staff nurse input regarding additional resources needed on the evening shift.

The FY’18 budgeting process used for Ellison 11 demonstrates how clinical nurse input and trended data of various types was used to budget direct care staffing FTEs. The monitoring of actual-to-budget performance for census, acuity, workload, and HPWI indicated an increased acuity and workload beyond budget targets. This trended information was used in planning for the FY’18 staffing budget, which will result in additional direct care FTEs for Ellison 11. Silva worked with clinical nurses to obtain their input into how the new nursing resources should be allocated, and incorporated their feedback into decisions regarding shift coverage changes for the Ellison 11 staffing schedule.

2017 Patients Care Link Data - Budget Staffing FY'17

Unit/Dept

FY'17 MN

Census Calc. HPPD

FY'17 RN

SH/24

FY'17 PCA

SH/24TOT

SH/24 D E NW/E

DW/E

EW/E

N D E NW/E

DW/E

EW/E

NEllison 11 30.20 9.66 29.5 6.9 36.5 13.0 11.5 6.5 11.0 9.0 6.0 3.5 2.8 1.0 3.0 2.5 0.5

2018 Patients Care Link Data - Planned Budget Staffing FY'18 (as of 5/15/17)

Unit/Dept

FY'18 MN

Census Calc. HPPD

FY'18 RN

SH/24

FY'18 PCA

SH/24TOT

SH/24 D E NW/E

DW/E

EW/E

N D E NW/E

DW/E

EW/E

NEllison 11 30.50 10.12 30.9 7.7 38.6 13.0 12.0 7.0 11.0 10.0 7.0 3.5 3.0 1.0 3.0 3.0 1.0

Staff Nurse Patient Care Associates

Staff Nurse Patient Care Associates

_______________________________________ From: Silva, Judith H., R.N. Sent: Friday, September 09, 2016 11:07 AM To: Cantave, Fredlyne; Chamberlain, Lea Marie; Daveiga, Elizabeth; Edouard, Kathleen; Farrell, Gabriella Gianna; Glinton, Yvonne; Kerr, Simone Patrice; Osmanov, Maria Isabel; Peoples, Shanelle; Restrepo, Stephanie; Riboul, Reynaldo C.; Shaddock, Christopher Martin; Tablouti, Najat; Bean, Suzanne V.,N.P.; Brown, Carol Therese,N.P.; Bryant, Jane, N.P.; Clark, Leslie C., N.P.; Davidson, Rebecca,N.P.; Finnegan, Andrea,N.P.; Gallagher, Sherrin L., N.P.; Gates, Rachel; Gimler, Therese,N.P.; Guttendorf, Ann,N.P.,M.S., R.N.; Lowry, Patricia A., N.P.; McDermott, Susan T.,N.P.; Nee, Catherine, R.N.; Pauley, Ainsley,R.N.;Salwierz, Ami L.; Silva, Judith H., R.N.; Stokes, Teresa,N.P.; Sullivan-Borah, Maura J., N.P.; Trecartin,Kelly E.,N.P.; Trifari, Lisa,N.P.; Wright, Nancy E., N.P.; Bell, Michelle M., R.N.; Belmar, Nancy S., R.N.;Benedetto, Joyce L., R.N.; Bergman, Monica J.,R.N.; Blanchet, Trinidad M.,R.N.; Boucher, Suzanne M.;Brown, Taylor G.,R.N.; Calvaresi, Samantha C.; Campbell, Olivia Taylor,R.N.; Cierpial, Chelby L., R.N.;Clark, Melissa M.,R.N.; Cordo, Kelly M.,R.N.; Crowley, Maura E.,R.N.; D'Antonio, Virgillia Rose; Dasinger,Hannah Burgess,R.N.; Debenedetto, Katherine Marie; Degnan, Stephanie A.,R.N.; DeMarco, ElizabethGilbert,R.N.; Dever, Jessica L.,R.N.; Doerrer, Judith L.,R.N.; Duval, Kristie Lee,R.N.; Dwyer, MaireadN.,R.N.; Ehnstrom, Erika D., R.N.; English, Mary,R.N.; Fallon-Smith, Mary,R.N.; Farias, Abigail E;Gallanaro, Arme D.; Genereux, Kristen Marie,R.N.; Givans, Peggy; Golden, Paul C.,R.N.; Gould, JohnJoel,R.N.; Grande, Madison Rae; Gregory, Pamela H.; Guerriero, Michelle Giovanna; Haldeman, Sioban,R.N.; Handerek, Eva M.; Hanly, Elizabeth A.,R.N.; Harris, Jared A.; Haynsworth, Kimberly R.,R.N.; Hulton,Jessica Louise,R.N.; Hunt, Amanda C.; Iandoli, Erin,R.N.; Jones, Khalea; Kebler, Mary L.,R.N.; Keenan,Erin E.,R.N.; Keough, Kelly A., R.N.; Kimball, Meredith L.,R.N.; Kindman, Mary L., R.N.; Larner, LauraCorrinne,R.N.; Larson, Elizabeth A., R.N.; Ma, Thu-Thao T.; Maggio, Michelle,R.N.; Marra, JenniferK.,R.N.; Mastaj, Brianne Sarah,R.N.; Mayville, Kerry; McColgan, Angela J., R.N.; McDonough, Heather L.,R.N.; McGrath, Shauna; McKeon, Clifford James,R.N.; McLaughlin, Kathleen A.,R.N. Ellison 11; Merritt,Erin E.,R.N.; Monahan, Nicole Ann,R.N.; Nguyen, Anna,R.N.; Noel, Emma; O'Donnell, Kristin L., R.N.;O'Leary, Kathryn; O'Meara, Catherine,MGH Case Mgmt; Osgood, Mary Elizabeth; Otis, Leann M., R.N.;Perez, Virginia I.; Perkins, Jessica R.,R.N.; Porazzo, Lisa, R.N.; Rainie, Stephanie,R.N.; Reilly, AmandaRegan; Riordan, Lindsey J.,R.N.; Roberts, Allen; Robinson, Julie R.; Roman, Jacqueline S.,R.N.; Rossiter,Molly Rose; Samatis, Kristen M.,R.N.; Schlageter, Christina Maire,R.N.; Schwalm, Julie A., R.N.; Schwartz,Brenda M., R.N.; Shafer, Deborah J., R.N.; Smith, Shelly; Socha, Laura H.,R.N.; Soucy, Jessica; St. Pierre,Nina R.,R.N.; Stewart, Dolores; Sullivan, Kayla; Sutera, Elizabeth,R.N.; Tarazi, Maura Madison.,R.N.;Taylor, Alycia Jean,R.N.; Viqueira Mendoza, Adriana K.,R.N.; Visnic, Emily E.; Vozikis, Barbara J., R.N.;White, Kathryn M.; Willis, Lisa; Yip, Brandon D; Zebertavage, Grace Helen,R.N.Subject: Staff Meeting 9/9/16

1. Thao Ma RN is starting on 9/19 with Courtney Schott NP on the same day. :-))

2. Please give stent cards to patients and not put them in the red charts! They may be in thecharts when they arrive or on top of the chart when they arrive. OA’S: Please do not put stentcards in the chart. Thanks. at the desk.

3. FINALLY, see the new Cardiac Surgery patient education booklets. I have left 2 on the tablein the back room.

4. On 9/23, there will be a Network upgrade happening at 2AM. Many of the phones andcomputers will be offline for about 90 minutes. The computers and phones that work willhave green tags on them that say “Online during network downtime”. They are able to keep upto 30 devices online during the upgrade, which would be a mix of phones, computers, and

printers. Biomed equipment is not affected. Bedside computers will be offline, but WOWs will still work.

5. We are missing a couple of Voalte phones. Please remember to sign them in and out andkeep a lookout for the 2 that are missing.

6. Please remember to direct your patients and families to the red folders at the bedside. Iknow you use them for discharge paperwork and education materials. But we have a newPatient Information book that is coming soon (just went to print) which we will soon include.The one currently in the folders is terribly outdated.

7. You will hear more about the new EPIC upgrade scheduled for 10/22. We will havedowntime from 1A to 5A. There are minor changes that we can review and there will, ofcourse, be a Healthstream.

8. Thank you for bringing the late admissions to my attention. I agree that since EPIC in April,we have later discharges and therefore, later admissions which puts tremendous pressure onthe evening staff. We sometimes have up to 11 admissions after 3PM. Many of you havementioned that it doesn’t seem to make sense to continue with the 12 hour evenings sinceadmissions are not coming by 11AM. You suggested that having that extra 4 hours would bebetter utilized from 3-7PM when more admissions arrive. This means more 12 hour day staffon which you all seem to agree would be a big change, especially for the 12 hour evening staff.However, the majority of staff feel that this is the best solution that we have to managing thelater admissions. We will continue to evaluate.

9. We will all have to complete our annual healthstream training between October 1 andDecember 30. Everyone is required to do this, even if you were recently hired.

10. Reminder: you do not need to give me a hard copy of your nursing license. It is monitoredon the web.

11. Safer Fair is October 19th 12-2P in the Bulfinch tent. The Collaborative GovernanceCommittees showcase their work. We have Leann Otis (Informatics); Jenn Marra (PatientEducation); Mairead Dwyer (Staff Nurse Advisory), Adrianna Viqueira (Diversity).

12. Fluid Trackers are printed and have arrived. There is a slot for them with our other forms.

Judy Silva RN MSN NE-BC Nursing Director Cardiac Interventional Unit Inpatient Cardiac Access Program Massachusetts General Hospital [email protected]

4.0 5.0 6.0 7.0 9.0 10.0 23.0 24.0

Unit/Dept

LOS ADJ

CENSUS

CLASS ACUITY YTD FEB

'17CLASS

WI

TOTAL ACUITY YTD FEB

'17TOTAL

WITARGET

HPWI SH/24RN % MIX

IN-DIRECT TIME %

FY 17 % RN

BENEFIT

FY 17 % NONRN BENEFIT

Cardiac SICU 14.3 3.411 48.8 3.569 51.0 7.00 44.7 87.0% 4.4% 16.1% 10.0%Ellison 8 30.0 1.719 51.6 1.855 55.7 5.65 39.3 80.0% 4.4% 10.4% 10.0%Ellison 9 - CCU 14.2 2.963 42.1 3.219 45.7 7.00 40.0 87.0% 4.4% 13.6% 10.0%Ellison 10 29.9 1.770 52.9 1.985 59.4 5.45 40.4 80.0% 4.4% 13.6% 12.7%Ellison 11 30.1 1.677 50.5 1.881 56.6 5.45 38.6 80.0% 4.4% 13.4% 10.0%SICU 16.1 3.495 56.3 3.626 58.4 7.00 51.1 87.0% 4.4% 16.8% 12.8%Blake 12 ICU 14.5 3.095 44.9 3.240 47.0 7.00 41.1 87.0% 4.4% 14.2% 10.0%Ellison 14 16.8 1.931 32.4 2.230 37.5 5.84 27.3 85.0% 4.4% 13.7% 10.0%Blake 6 15.6 1.662 25.9 1.933 30.2 5.20 19.6 80.0% 4.4% 14.9% 15.6%White 7 21.5 1.895 40.7 2.307 49.6 5.20 32.2 80.0% 4.4% 15.1% 10.0%Ellison 7 28.9 1.810 52.3 2.068 59.8 5.20 38.8 80.0% 4.4% 14.7% 10.0%Ellison 19 23.0 1.697 39.0 1.925 44.3 5.20 28.8 80.0% 4.4% 15.5% 10.0%Phillips House 22 16.7 1.772 29.6 1.977 33.0 5.20 21.5 80.0% 4.4% 12.2% 10.0%Bigelow 14 22.8 1.618 36.9 1.789 40.8 5.20 26.5 80.0% 4.4% 12.0% 10.0%Blake 7 - MICU 16.1 3.375 54.3 3.687 59.4 7.00 51.9 87.0% 4.4% 12.0% 10.0%Ellison 16 29.1 1.875 54.6 2.061 60.0 5.20 39.0 80.0% 4.4% 16.4% 10.0%Phillips House 20 19.0 1.731 32.9 2.015 38.3 5.20 24.9 80.0% 4.4% 14.3% 12.8%Bigelow 13 RACU 11.4 2.241 25.5 2.380 27.1 5.84 19.8 87.6% 4.4% 13.2% 10.0%Bigelow 9 Medicine 16.5 1.520 25.1 1.786 29.5 5.20 19.2 80.0% 4.4% 11.8% 10.0%Bigelow 11 22.4 1.739 39.0 2.001 44.8 5.15 28.9 99.0% 4.4% 13.7% 10.0%White 9 21.2 1.717 36.4 2.006 42.5 5.20 27.6 80.0% 4.4% 10.6% 10.0%White 8 23.0 1.686 38.8 1.908 43.9 5.20 28.5 80.0% 4.4% 10.6% 11.9%White 10 17.6 1.814 31.9 2.104 37.0 5.20 24.1 80.0% 4.4% 13.3% 10.0%White 11 21.6 1.763 38.1 1.911 41.3 5.20 26.8 80.0% 4.4% 12.2% 10.0%Ellison 12 31.2 1.497 46.7 1.692 52.8 5.20 34.3 80.0% 4.4% 10.0% 10.0%Lunder 9 30.6 2.142 65.5 2.390 73.1 5.20 47.5 80.0% 4.4% 12.3% 10.0%Lunder 10 30.5 2.284 69.7 2.416 73.7 5.45 50.2 83.5% 4.4% 15.4% 10.0%White 6 24.3 1.774 43.1 1.975 48.0 5.20 31.2 80.0% 4.4% 13.9% 10.3%Ellison 6 26.8 1.773 47.5 2.034 54.5 5.20 35.4 80.0% 4.4% 15.2% 10.3%Lunder 6-Neuro ICU 19.4 2.817 54.6 2.986 57.9 7.00 50.7 87.0% 4.4% 17.5% 10.0%Lunder 8 30.0 2.025 60.8 2.229 66.9 5.20 43.5 80.0% 4.4% 12.8% 11.0%Lunder 7 29.2 1.987 58.0 2.268 66.2 5.20 43.0 80.0% 4.4% 15.5% 10.0%Blake 11 23.3 1.520 35.4 1.622 37.8 6.07 28.7 69.0% 4.4% 16.3% 14.0%PICU 9.6 2.325 22.3 2.486 23.9 7.95 23.7 95.0% 4.4% 13.5% 10.0%Ellison 17 14.7 1.842 27.1 2.080 30.6 5.20 19.9 80.0% 4.4% 15.3% 10.0%Ellison 18 16.7 1.854 31.0 2.264 37.8 5.20 24.6 80.0% 4.4% 14.8% 10.0%Phillips House 21 17.0 1.702 28.9 1.929 32.8 5.20 21.3 80.0% 4.4% 17.5% 10.0%NICU 15.1 2.466 37.2 2.509 37.9 7.00 33.2 95.0% 4.4% 16.4% 14.2%Ellison 13 29.7 1.743 51.8 2.008 59.6 4.95 36.9 96.0% 4.4% 14.9% 10.0%Blake 13 30.9 1.271 39.3 1.609 49.7 4.25 26.4 99.0% 4.4% 15.4% 16.0%TOTAL 871.3 1.950 1,699.4 2.176 1,895.8 5.62 1,331.1 83.5% 4.4% 14.1% 10.6%

Classification Unit Data FY'18

..................................................................................................................................................... From: Gallivan, Theresa M., R.N. Sent: Monday, January 09, 2017 11:52 AM To: Bethune Regan, Cristina M.; Donahue, Vivian E.; Fitzgerald, Patricia A., R.N.; Gonzalez, Colleen E, R.N.; Hall, Kathryn E.; Hughes, Maryfran, R.N.; Johnson, Stacy Hutton,R.N.; Joseph, Melissa,R.N.; Livelo,Jeanette N.,R.N.; McEachern, Donna; McKenna, Sharon; Mills, Jennifer C.,R.N.; Morash, Susan, R.N.;Moulaison, Walter J.,R.N.; Sargent, Jennifer L.,R.N.; Schnider, Maureen E.,R.N.; Silva, Judith H., R.N.;Sylvia-Reardon, Mary H.,R.N.; Tata, Lee Ann,R.N.; Tubridy, Aileen, R.N.; Winne, Maria D., R.N.Cc: Annese, Christine Donahue, R.N.Subject: Please review

Attached are the proposed FY 18 direct care changes to the budget (Partners 2.0 effort toward 44 million reduction) built on reducing HPWI and the allocation of observer workload to PCAs (changes skill mix).

The last column reflects the unit level changes and the impact with RN reductions and PCA adds.

Would you please review, assess impact on overall staffing pattern, and let Chris Annese and I know if you believe the changes will not be workable or you have questions.

We can touch on this when we meet later this week but helpful to know in advance of any major concerns.

Thank you and we are in process of scheduling a Partners 2.0 presentation for the NDs. Theresa

Theresa Gallivan, RN, MS, NEA-BC Associate Chief Nurse Massachusetts General Hospital 55 Fruit Street, Founders 348 Boston, MA 02114 phone 617.724.1767 e-mail [email protected]

Promoting Excellence Every Day through knowledge and compassion mghpcs.org/EED

......................................................................................................................................

From: Silva, Judith H., R.N. Sent: Monday, January 09, 2017 12:00 PM To: Annese, Christine Donahue, R.N. Subject: FW: Please review Hi Chris, I understand the need for reductions. I would just point out that YTD, Ellison 11 is the only Cardiac Unit and one of the only medical units that is significantly above budget in workload. Judy .................................................................................................................................................. From: Raye, Nancy J., R.N. Sent: Tuesday, January 10, 2017 11:54 AM To: Silva, Judith H., R.N. Cc: Annese, Christine Donahue, R.N. Subject: Let Me Allay Your Fears a Bit I am including Chris because she called this morning with some of the concerns expressed. I suggested that she not forget that your current increase in acuity and possibly census will still go forward in the model and result in additional staffing as needed. For example, I have included your FY’17 budget here......and I changed to show what it would look like if I used your October through December actual values for census and acuity (which is what I will be doing in the budget process except it will be YTD February). That increases your staffing by 3.3 FTEs (2.9 RNs). So the system is picking up your increased workload. If I reduce your HPWI from 5.50 to 5.45, it means you would get an additional 2.8 FTEs (2.5 RNs). So my guess is that you would still try to hire 3 RNs or so in either model. I hope this helps.

Massachusetts General HospitalPatient Care ServicesFY'2018 Personnel Budget (Pending Final Approval)

Nursing Director: Judy Silva

Ellison 11 CAU

Description FY'17 FY'18 Diff.

Beds 36.0 36.0 0.0

Occupancy % 83.9% 84.7% 0.8%

Midnight ADC 30.2 30.5 0.3

Classification ADC 29.6 30.1 0.5

Classification Acuity 1.604 1.677 0.073

Classification Workload Index 47.5 50.5 3.0

Total Acuity 1.792 1.881 0.089

Total Workload Index 53.0 56.6 3.6

Hours / Workload Index 5.50 5.45 (0.05)

Shifts / 24 Hours 36.5 38.6 2.1

Indirect Time 4.5% 4.4% -0.1%Benefit Time RN 14.3% 13.4% -1.3%Benefit Time Non-RN 3.2% 10.0% -2.8%

Direct Care FTEs - WI 59.9 63.5 3.6

CNS Direct Care 0.1 0.4 0.3Staff Nurse 49.3 50.7 1.4Non RN Direct 10.5 12.4 1.9Total Direct Care FTEs 59.9 63.5 3.6

Leadership 3.0 2.7 (0.3)Other RN 10.1 11.3 1.3Op. Assoc. 7.5 7.1 (0.4)Unit Assist/ USA 6.8 6.8 0.0Other Support 0.0 0.0 0.0Other Non-RN 0.0 0.0 0.0Other FTEs 27.4 28.0 0.6

Total FTEs 87.3 91.5 4.2