Secondary Logo

Journal Logo

Original Studies

The Process of Implementing a Mobility Technician in the General Medicine and Surgical Population to Increase Patient Mobility and Improve Hospital Quality Measures

A Pilot Study

Exum, Emelia; Hull, Brian L.

Author Information
Journal of Acute Care Physical Therapy: October 2019 - Volume 10 - Issue 4 - p 129–138
doi: 10.1097/JAT.0000000000000110
  • Free

Abstract

Decreasing unnecessary bed rest in the acute care setting has been an area of focus in hospitals for the past 2 decades.1–7 The concept of hospital-associated/acquired disability (HAD) is described in the literature as a decrease in muscle strength, muscle mass, cognitive function, muscle protein synthesis, and physical function.8 Although a definitive causal link is not established between the concept of HAD and rise in postacute care (PAC) disability that outlasts the reason for the hospital admission, the associated symptoms do lead to increased physical limitations. Those physical limitations decrease the ability to return home following an acute care hospital stay.8,9 This disability and dysfunction costs health care systems significant amounts of money negatively impacting margins.9,10 In addition, payment practice changes toward value-based purchasing (VBP) and bundled payments have added pressures on hospitals creating a greater need to reduce hospital-acquired conditions and PAC spending. The Centers for Medicare & Medicaid Services' VBP program financially incentivizes hospitals for improving quality measures including improved patient experience and decreased HAD improving hospital margins.11 Decreasing HAD and improving patient satisfaction and experience will lead to higher reimbursement and hospital savings.12–14

Unnecessary bed rest along with increasing medical complexity and comorbidities is associated with greater disability, with medical admissions to the acute care setting.9,15 The literature is clear on the importance of preventing many of the adverse outcomes associated with immobility such as pressure injuries, deep venous thrombus and pulmonary embolism, and muscle weakness.8 However, Houlihan et al16 discussed how the mobility of patients on a general medicine floor is placed at lower priority by nursing and reserved for the end of the hospital admission due to perceived concerns with nursing confidence and patient safety. Furthermore, Brown et al17 concluded that older adults spent up to 83% of their hospital stay in bed and just 0.20% to 21% of time spent standing or ambulating. The literature is also clear on the importance of early mobility to improve clinical outcomes, with emphasis placed on early mobility in intensive care units.8,18–20 However, the literature is not as robust in discussing the importance of progressive mobility, which is increasing and maintaining mobility for patients in the general medicine and surgical nonintensive care unit.

Many hospital fall prevention programs, designed to keep patients safe, inadvertently cause disability by keeping them immobile for prolonged periods.21 As a result, a considerable number of patients do not complete any ambulation during their inpatient stay and those, who do ambulate, do not ambulate outside of their room.8 This excessive amount of bed rest may be contributing to preventable harm known as HAD or PAC syndrome, which can also lead to increased and expensive PAC rehabilitation utilization.8,12

To mitigate the effects of prolonged bed rest, a referral is often made to physical therapy for unskilled physical therapy service, which can add unnecessary hospital expense and divert limited physical therapy resources away from patients in need. Physical therapists are skilled professionals at identifying and managing both medical and physical health limitations; however, the finite staffing resources limit the ability of these clinicians to oversee all general medical and general surgical unit patient mobility. In addition, this level of skilled care is not required for basic patient mobility and reduces the amount of time therapists can spend treating patients with significant needs. To provide the best care for the patient, and to prevent the overutilization of therapy services, the bedside nursing team must also be involved.12,16 We propose that an unlicensed technician can work under the supervision of nursing to fill the mobilization needs of patients who do not require skilled therapy resources or as an adjunct for those receiving skilled therapy services.

The authors created a quality improvement patient mobility pilot program designed to minimize unnecessary bed rest and subsequent hospital-acquired physical disability for patients who come into the hospital with minimal to no physical disability. The 3-month mobility technician (MT) pilot study aimed at gathering mobility data, along with patient satisfaction, fall rate, length of stay (LOS), and PAC discharge rate. The end goal would be a change in the acute care hospital's culture to emphasize the need for increased patient mobility on a regular basis with the intention of progressing each patient to their highest achievable level without simply relying on additional skilled physical therapy.12

To our knowledge, little to no research has been published on the cost-benefit analysis of implementing an MT or team in the nonintensive care inpatient acute setting, with the goal of decreasing HAD. This study aims to describe the MT implementation process and the observed effects on patient mobility. The study also examines the resulting effects on patient experience, reducing HAD, evident through shorter LOS and less PAC rehabilitation needed while not increasing falls or other adverse events.

METHODS

The mobility pilot (MP) program was conducted at Baylor University Medical Center a 1025-bed academic teaching hospital with a level 1 trauma center status. Between July 2017 and November 2017, the Physical Medicine and Rehabilitation (PMR) Department, in collaboration with a medical and a surgical nursing unit, created the MP program. For this study, PMR refers to both physical therapy and occupational therapy. The program was designed to address the patient population without significant mobility deficits prior to admission, but who were not independent with mobility during hospitalization. A PMR department therapy-trained technician, with 14 years of therapy technician experience, was selected as MT to work under nursing supervision for the MP. The MT received training on safe patient handling and in the use of safety equipment such as the gait belt, applying grip socks, and proper use and adjustment of a rolling walker from a licensed physical therapist. For this study, the MT received the patient list from the nursing-designated location on the unit. The MT would then identify the patient's current Johns Hopkins Highest Level of Mobility (JH-HLM) score located on the patient list and mobilize that patient with the goal of increasing the mobility score a minimum of 1 level each day on the JH-HLM scale. The JH-HLM is a validated tool to quantify the highest patient mobility level on a scale from 1 to 8 (see Figure 1). While the JH-HLM reliability and sensitivity have not been established, the scale's purpose is as a shared communication tool between physicians, nursing, therapy, and unlicensed patient care technicians. Each time the patient is mobilized by nursing or therapy staff, the patient receives a highest level of mobility achieved score. Following the initial JH-HLM score, the patient is given a goal to progress their mobility 1 level each day. Having the shared interdisciplinary mobility scale along with a shared goal to advance mobility levels each day, the entire patient care team unites to decrease unwarranted bed rest.22

FIGURE 1
FIGURE 1:
Johns Hopkins Highest Level of Mobility Scale.

The MP occurred from December 4, 2017, to March 2, 2017. The MT spent 4 hours daily on each unit, mobilizing patients deemed appropriate by the nursing staff. Each nurse, based on his or her shift assessment, would screen each patient for medical stability and safety to participate in mobility that day. If deemed appropriate for the MP, selected patients were assessed a pre-MT JH-HLM mobility score by the bedside nurse using a progressive mobility algorithm, and then placed on the MT schedule (see Figure 2).12,22 The progressive mobility algorithm is designed for the nursing staff to systematically take each patient through mobility tasks to establish the patients' highest level safely achieved on admission to the unit. This systematic approach assists the nursing staff with assigning the appropriate JH-HLM score. The MT's goal was to increase the level of mobility of each patient at least 1 JH-HLM level each session. The MT would then mark the JH-HLM postscore achieved during their session and at the end of the time on that unit, return the data to the designated nursing representative to be documented into the medical record.

FIGURE 2
FIGURE 2:
Guide to Progressive Mobility Algorithm.

Each day the MT tracked the time spent with each patient, pain level, JH-HLM pre- and postscore, beginning and ending patient position and that the call light was within reach. At discharge from the inpatient acute care setting, the discharge location of each patient was recorded. Other outcomes tracked during this MP were falls, patient satisfaction scores, changes in LOS, and MP cost.

RESULTS

The MP study was completed over a 3-month period excluding weekends (65 days). The sample included 954 patients between the 2 units. The MP group consisted of 292 patients—140 general medicine (GM) and 152 general surgical (GS). The baseline data group consisted of 662 patients (429 GM and 233 GS). During this pilot, 622 patient encounters occurred (329 GM and 293 GS). The MP group was 48% male on the GM unit and 38% male on the GS unit. The average age for the MP group on the GM unit was 64.4 (24-97) years and for the GS unit 59.1 (15-99) years. The MP group for the GM unit was 37% African American, 48% Caucasian, 12% Hispanic (nonblack), and 3% other. The MP group for the GS unit was 23% African American, 70% Caucasian, 6% Hispanic (nonblack), and 1% other. The severity of illness, which we used to assess the level of acuity on the unit during the pilot, was 2.65 on the GM unit and 2.18 on the GS unit. The most common admitting diagnoses for the GS unit were abdominal pain with a surgical procedure, morbid obesity with weight loss surgery, and head and neck cancer with surgical intervention. The most common medical comorbidities on the GS unit were diabetes mellitus type 2, hypertension, coronary artery disease, chronic kidney disease, and cancer of various types. The most common admitting diagnoses for the GM unit were sepsis, chronic obstructive pulmonary disease exacerbation, cellulitis, and abdominal pain. The most common medical comorbidities on the GM unit were diabetes mellitus type 2, hypertension, coronary artery disease, congestive heart failure, and chronic obstructive pulmonary disease exacerbation. The admitting diagnosis and comorbidities from both units have been linked to HAD.8

The average ratio of nurse to patient on the GM unit was 5:1 and on the GS unit 4:1. The ratio of nursing assistant to patient is 9:1. The average number of patient visits seen each day by the MT was 12 visits per 8-hour shift, with an average contact time of 15.5 minutes on the GM and 16.4 minutes on the GS. The total distance ambulated by all included patients during this pilot was 68 020 ft or 12.9 miles on the GM unit and 70 900 ft or 13.4 miles on the GS unit. The average distance ambulated per patient was 221.84 ft on the GM unit and 260.58 ft on the GS unit. When assessing for salary and benefits cost for the MT, this average number of visits comes to $14.77/visit.

While the JH-HLM does not have an established minimal clinically important difference, the authors assigned the MT a simple goal of increasing the JH-HLM score 1 level on each visit. The average change in JH-HLM score per visit, excluding patients with a prescore of 8, which is the highest score, was 1.22 (1.25 on the GM unit and 1.19 on the GS unit) (see Table 1).

TABLE 1
TABLE 1:
Mobility Technician Pilot Costs and Activity Produced

In addition, an increase occurred in Press Ganey Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) Rating of the Hospital metric, on the GM unit compared with the baseline data of 9.19% and an increase in the HCAHPS Responsiveness of Staff score on both units with 37% for the GM unit and 16.47% on the GS unit. Falls did not increase on the GS unit. The average number of falls on the GM unit before the pilot was 15 falls in 3 months of the baseline data that decreased to 7 falls total in 3 months. Important to this project, note that no falls occurred on either unit associated with the MT during the MP pilot. The LOS decreased during the first full month of the MP by 0.54 days on the GM unit, and by 0.30 days on the GS unit. Finally, 89% of GM patients who worked with the MT discharged home compared with 83% of control group patients. The GS patients participating in the study discharged home 83% of the time compared with 90% for the baseline data group (see Table 2). In this study, the patients working with the MT were not precluded from working with PMR. The percentage of patients that discharged home that did not have PMR services was 70% on the GM unit and 86% in the GS unit.

TABLE 2
TABLE 2:
Changes in Discharge Disposition

The χ2 test was used to assess the expected change between the pilot results compared with the baseline data from 3 months prior to the pilot. Based on the premise that the only observable variable that changed was the addition of the MT, any changes in the agreed-upon parameter could be attributed to the MT. For this pilot, we chose a significance value of 0.05. At this level of significance, the data collected on LOS, Press Ganey HCAHPS hospital comparison scores of Staff Responsiveness and Rating of Hospital, JH-HLM scores, falls, and discharge disposition were found not to be significant.

DISCUSSION

This pilot aimed to describe the implementation processes of a designated MT, providing daily mobility on a medical and surgical acute care unit.

The observed pilot results of decreased LOS, increased patient satisfaction, with no increase in falls, although not statistically significant, are encouraging and do provide some further areas for discussion and study. The authors also found the potential for cost savings and other improvements in hospital quality metrics. Hospitals improving patient satisfaction and experience, and decreasing HAD, are eligible for increased reimbursement through VBP.

During this quality improvement pilot, the goal was to minimize any other variable changes in the daily workflow of the units including therapy consultation practices, with the exception of adding the MT resource. The authors were unable to control for other variables such as patient population, diagnosis, comorbidities, and social factors. This level of control is difficult in acute care, and for the scope of this quality improvement pilot was not crucial. In order for this pilot study to be reproducible in a GM and GS population, controlling for every variable would inadvertently make it less reproducible.

The authors found that 70% of the patients on the GM unit and 74% on the GS unit who discharged home in this cohort did not receive PMR services, which partially isolates the contribution of PMR to increasing the discharge to home rate. The authors also observed that the higher the JH-HLM score, the more likely patients would discharge to home. On the GM unit, 90% of the patients who went home had a JH-HLM score of 7 or 8 and 91% of the patients who went home on the GS unit had a JH-HLM score of 7 or 8. This observation is an important premise, as the goal of the culture change for increased mobility is not to simply increase patient mobility. The goal is to return patients to their preadmission, baseline level of mobility, increasing the chance of returning home. Enabling more patients to return home safely decreases preventable PAC utilization for patients without a skilled medical PAC need. Although the JH-HLM score change is not statically significant, the MP's goal of increasing the patients' mobility at least 1 level on the mobility scale was achieved during this pilot.

The data collected were compared against normative data 3 months prior to the pilot for both units and then during the pilot for all patients on the unit. The MP data account for approximately 31% of patients with recorded discharge information for both units combined (14% GM unit and 16% GS unit). We observed a 6% increase in patients discharged home on the GM unit and a decrease of 7% in the GS unit. The reason for the decrease in the percentage of patients who discharged home during this period is not known, but the severity of illness did increase 4.31% from the previous 3 months suggesting a higher patient acuity during the MP.

When adjusting for the estimated cost of patients using these PAC facilities, we can see the total expense. During the span of this pilot, all PAC spending totaled an estimated $2 587 494 (see Figure 3). The largest PAC discharge facility group was skilled nursing facilities. When compared with the total pilot costs of $9185, preparing just one more patient for a safe discharge home can make a significant effect on decreasing the cost related to PAC utilization.

FIGURE 3
FIGURE 3:
Postacute Care Spending Comparison. CG indicates, control group; MP, mobility pilot.

Other cost-saving initiatives that hospital organizations use are related to hospital rating scores. During this pilot, we observed the changes in the Press Ganey HCAHPS scores for Responsiveness of Staff and Rating of Hospital (refer to Table 3). We cannot state that the increase in the Press Ganey HCAHPS scores was directly correlated with the implementation of the MT; however, with reimbursement being closely linked to HCAHPS scores through VBP, being able to associate a change in increasing patient mobility to increasing patient satisfaction during this MP was an unforeseen potential financial saving.

TABLE 3
TABLE 3:
Pilot Study Outcomes

The authors found multiple opportunities to expand and improve on the MP results. This level 1 trauma center has a minimum of 7 nonintensive care units matching many of the criteria of the units in the MP. These similarities encourage us that more work can be done to increase mobility in the hospital and potentially decrease the PAC cost simultaneously.

Another area for MP improvement would be to maximize the efficiency of this type of program. The average number of patient visits by the MT per 8 hours was 12 visits. We feel that this number is low based on the average amount of time spent with each patient being 15.9 minutes between both units. At this figure of 15.9 minutes per encounter, a fully productive MP program could see 18 visits per 8 hours and thus decrease the cost per visit from $14.77 to $9.67 per visit. The MT saw a total of 292 unique patients during this pilot with 622 visits recorded with a potential of 950 visits over 3 months. The combined recorded patient contact minutes were 9902 minutes during the MP. At full productivity, the MT could complete 15 127 minutes (951 visits) in the same amount of time.

Last, the authors identified a lack of consistency in the assessment of patient function at admission, with minimal to no lag time in initiating mobility in those who were stable. While measuring the time from admission to initiation of assessment and subsequent mobility on each unit was outside the scope of this pilot, the authors did note anecdotal delays. The authors propose that if mobility could be initiated as early as medically possible during an inpatient acute care stay and maintained on a regular basis, we could see a decreased overall need for PAC rehabilitation in patients who came from home and were relatively mobile at baseline.

LIMITATIONS

Due to several limitations related to smaller sample size, short pilot duration, and limited demographics of the baseline data group, we are unable to draw a definitive conclusion from the observed results. However, the process of implementing an MT is valuable to discuss, as the concept itself has the potential to improve general medical and general surgical population patient mobility.

The first pilot study limitation was the increase in hours for education during the pilot's first month. Although education was provided to the nursing staff, it was not hardwired into their daily practice. While the data were collected over a 3-month period, the authors conceded that the first month of data might be skewed due to the need for continued education and follow-through. The next limitation was the rotating staffing schedule with new nurses every 2 to 3 days, and the need to reeducate each new nurse on the process daily.

In addition, due to the nature of this pilot design, the authors were unable to adequately control for demographics in the baseline data group and to determine how many of those patients received therapy intervention. Although patients were mobilizing with the MT and with PMR staff, the premise of the pilot was to maximize the mobility of patients on the unit and not compare skilled PMR intervention to nonskilled MT mobility. The MP group was not randomized as the nurses placed patients on the list each morning, but this was blinded from the MT. Also, controlling for patients having changes in medical status and medical procedures was not within the scope of this pilot. The authors felt that since changes in medical status and medical procedures are common and difficult to exclude in the general population, removing such data points would further skew the data and any significance that was obtained.

FUTURE CONSIDERATIONS

The authors recommend future research examine the MP on a larger scale to better examine change significance with discharge disposition, LOS, patient satisfaction HCAHPS scores, and falls. In addition, future studies should control for and compare immobility-related sequelae such as skin breakdown, venous thromboembolism, pneumonia, and orthostatic hypotension. Finally, the authors recommend investigators examine changes and correlations between PMR utilization during and after MT implementation to assess whether MT implementation will lead to more effective and appropriate skilled PMR usage.

MT selection is essential to the success of the program. Candidates must be adequately trained to interact with not only the patients on the specific units but also the interdisciplinary staff. In addition, MT candidates should possess effective communication, resilience, dependability, attention to detail, and follow-through. MT clinical training should emphasize safe patient-handling techniques for all aspects of patient mobility, effective use of all lifting and mobility equipment, and a basic understanding of changes in patient status.

The selection of the GM and GS units was also strategic. The authors selected units with a prior interest in mobility initiatives and were equally interested in implementing programming that would increase patient mobility and decrease falls. The support of the nursing leadership and nursing staff was imperative to the success of the MP and allowed for greater compliance with the data collections as the MP progressed.

The authors estimate the MT has the capacity to see 8 patients in the morning and 8 in the afternoon based on 30-minute patient blocks. Due to the fluctuating census, educational gaps in the use of the JH-HLM and compliance, the MT was less productive some days than expected. In an effort to improve the MT productivity and to account for fluctuating census and compliance, the authors suggested to both units that the MT could see the same patients each day they were in the inpatient acute care setting if they were assessed as medically appropriate to participate in mobility. The authors also explained to nursing participants that even if the patients were on therapy caseload, they could be on the MT schedule for additional mobility. Future investigators should pay particular attention to collaboratively developing MP education for nursing unit personnel.

CONCLUSION

The MP is a promising tool for increasing patient mobility in the nonintensive care GM and GS setting, while potentially decreasing the need for PAC rehabilitation for many patients with minimal mobility deficits. Although the observed changes were not statistically significant, the authors recommend further study controlling for the limitations identified and designed to capture higher-powered results observed in this pilot. This type of program shows promise for decreasing LOS and increasing patient satisfaction without increasing fall rates. Hardwiring the concept of progressive mobility into daily practice combined with a basic, interdisciplinary assessment of mobility will provide the foundation needed to create a culture of mobility that will benefit all patients. The addition of an MT designated to provide regular, progressive nurse-supervised mobility along with an interdisciplinary mobility assessment tool such as the JH-HLM is the potentially missing piece to the current challenges of unnecessary bed rest in hospitalized patients.

REFERENCES

1. Adler J, Malone D. Early mobilization in the intensive care unit: a systematic review. Cardiopulm Phys Ther J. 2012;23(1):5–13.
2. Kayambu G, Boots R, Paratz J. Physical therapy for the critically ill in the ICU. Crit Care Med. 2013;41(6):1543–1554. doi:10.1097/ccm.0b013e31827ca637.
3. Stiller K. Physiotherapy in Intensive Care. Chest. 2013;144(3):825–847. doi:10.1378/chest.12-2930.
4. Hopkins RO, Spuhler VJ, Thomsen GE. Transforming ICU culture to facilitate early mobility. Crit Care Clin. 2007;23(1):81–96. doi:10.1016/j.ccc.2006.11.004.
5. Thomsen GE, Snow GL, Rodriguez L, Hopkins RO. Patients with respiratory failure increase ambulation after transfer to an intensive care unit where early activity is a priority. Crit Care Med. 2008;36(4):1119–1124. doi:10.1097/ccm.0b013e318168f986.
6. Morris PE. Moving our critically ill patients: mobility barriers and benefits. Crit Care Clin. 2007;23(1):1–20. doi:10.1016/j.ccc.2006.11.003.
7. Morris PE, Goad A, Thompson C, et al Early intensive care unit mobility therapy in the treatment of acute respiratory failure. Crit Care Med. 2008;36(8):2238–2243. doi:10.1097/ccm.0b013e318180b90e.
8. Falvey JR, Mangione KK, Stevens-Lapsley JE. Rethinking hospital-associated deconditioning: proposed paradigm shift. Phys Ther. 2015;95(9):1307–1315. doi:10.2522/ptj.20140511.
9. Ensrud KE, Lui L-Y, Langsetmo L, et al Effects of mobility and multimorbidity on inpatient and postacute health care utilization. J Gerontol A Biol Sci Med Sci. 2018;73(10):1343–1349. doi:10.1093/gerona/glx128.
10. Soley-Bori M, Soria-Saucedo R, Ryan CM, et al Functional status and hospital readmissions using the medical expenditure panel survey. J Gen Intern Med. 2015;30(7):965–972. doi:10.1007/s11606-014-3170-9.
11. Health Catalyst. Value-Based Purchasing: 4 Need-to-Know Domains for 2018. https://www.healthcatalyst.com/insights/value-based-purchasing-4-need-to-know-domains-2018. Published May 15, 2018. Accessed March 25, 2019.
12. Wald HL, Ramaswamy R, Perskin MH, et al The case for mobility assessment in hospitalized older adults: American Geriatrics Society White Paper Executive Summary. J Am Geriatr Soc. 2019;67(1):11–16. doi:10.1111/jgs.15595.
13. Vertrees J, Averill R, Eisenhandler J, Quain A, Switalski J. Bundling post-acute care services into MS-DRG payments. Med Med Res Rev. 2013;3(3):E1–E19. doi:10.5600/mmrr.003.03.a03.
14. Hardin L, Kilian A, Murphy E. Bundled payments for care improvement. J Nurs Adm. 2017;47(6):313–319. doi:10.1097/nna.0000000000000492.
15. Hong J, Lee WK, Kim MK, Lee BE, Shin SD, Park H. Effect of comorbidity on length of hospital stay and in-hospital mortality among unintentionally injured patients. Accid Anal Prev. 2013;52:44–50. doi:10.1016/j.aap.2012.12.007.
16. Houlihan S, Fernandez N, Magnant C, Levin A, Murphy S. Evaluating a nurse-driven mobility algorithm for hospitalized general medicine patients: a pilot study. J Acute Care Phys Ther. 2018;9(4):179–185.
17. Brown CJ, Redden DT, Flood KL, Allman RM. The underrecognized epidemic of low mobility during hospitalization of older adults. J Am Geriatr Soc. 2009;57(9): 1660–1665.
18. Drolet A, Dejuilio P, Harkless S, et al Move to improve: the feasibility of using an early mobility protocol to increase ambulation in the intensive and intermediate care settings. Phys Ther. 2012;93(2):197–207. doi:10.2522/ptj.20110400.
19. Engel HJ, Needham DM, Morris PE, Gropper MA. ICU early mobilization. Crit Care Med. 2013;41(9):S69–S80. doi:10.1097/ccm.0b013e3182a240d5.
20. Hopkins RO, Miller RR, Rodriguez L, Spuhler V, Thomsen GE. Physical therapy on the wards after early physical activity and mobility in the intensive care unit. Phys Ther. 2012;92(12):1518–1523. doi:10.2522/ptj.20110446.
21. Growdon ME, Shorr RI, Inouye SK. The tension between promoting mobility and preventing falls in the hospital. JAMA Intern Med. 2017;177(6):1–4. doi:10.1001/jamainternmed.2017.0840.
22. Hoyer EH, Friedman M, Lavezza A, et al Promoting mobility and reducing length of stay in hospitalized general medicine patients: a quality-improvement project. J Hosp Med. 2016;11(5):341–347. doi:10.1002/jhm.2546.
© 2019 by Lippincott Williams & Wilkins, Inc.