Telehealth-based transitional care management programme to improve access to care

Abstract

Background

The transition from hospital to home is a vulnerable time for patients and families that can be improved through care coordination and structured discharge planning.

Local problem

Our organisation aimed to develop and expand a programme that could improve 30-day readmission rates on overall and disease-specific populations by assessing the impact of a telehealth outreach by a registered nurse (RN) after discharge from an acute care setting on 30-day hospital readmission.

Methods

This is a prospective observational design conducted from May 2021 to December 2022 with an urban, non-academic, acute care hospital in Westchester County, New York. Outcomes for patients discharged home following inpatient hospitalisation were analysed within this study. We analysed overall and disease-specific populations (congestive heart failure (CHF), chronic obstructive pulmonary disease (COPD) and pneumonia (PNA)) as compared with a 40-month prestudy cohort.

Intervention(s)

Patients were identified in a non-random fashion meeting criterion of being discharged home after an inpatient admission. Participants received a telephonic outreach by an RN within 72 hours of discharge. Contacted patients were asked questions addressing discharge instructions, medication access, follow-up appointments and social needs. Patients were offered services and resources based on their individual needs in response to the survey.

Results

68.2% of the 24 808 patients were contacted to assess and offer services. Median readmission rates for these patients were 1.2% less than the prestudy cohort (11.0% to 9.8%). Decreases were also noted for disease-specific conditions (CHF (14.3% to 9.1%), COPD (20.0% to 13.4%) and PNA (14.9% to 14.0%)). Among those in the study period, those that were contacted between 24 and 48 hours after discharge were 1.2 times less likely to be readmitted than if unable to be contacted (254/3742 (6.8%) vs 647/7866 (8.2%); p=0.005).

Conclusions

Using a multifaceted telehealth approach to improve patient engagement and access reduced 30-day hospital readmission for patients discharged from the acute care setting.

Correspondence to Michelle Elsener; [email protected]

WHAT IS ALREADY KNOWN ON THIS TOPIC

• The transition in care from an acute care setting to home is a vulnerable period for patients and families. Transitional care management programmes have been developed as a bridge to reduce gaps and improve coordination of care, but the literature on its impact is varied, particularly its impact on 30-day hospital readmission.

WHAT THIS STUDY ADDS

• We developed an internally funded multidisciplinary telehealth approach for transitional care management to increase access to care and services for patients and families after discharge from the acute care setting. With the evolution of the programme, our observational data demonstrate a decrease in readmissions for the overall population, as well as disease-specific conditions including congestive heart failure, chronic obstructive pulmonary disease and pneumonia.

HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY

• With increasing focus on improving population health and reducing hospital readmissions, transitional care teams are being developed and expanded with limited access to research to support clinical workflows. This study provides a single-centre use of telehealth and a multidisciplinary community collaborative approach to address barriers to care for patients with hospital readmission as a surrogate marker for preventable harm.

Introduction

Problem description

Transitions in care, specifically from hospital to home, mark a vulnerable period for patients and caregivers.^{1 2} This period is typified by potentially actionable occurrences involving worsening symptoms,^{3 4} medication non-adherence,⁵ lack of follow-up testing,⁶ rehospitalisations⁷ and emergency department (ED) visits.⁸

Available knowledge

Transitional care management (TCM) programmes have been developed to reduce gaps in care experienced by patients after acute care hospitalisation. Programmes such as the Transitional Care Model,⁹ Project RED (Re-engineered Discharge),¹⁰ Care Transitions Interventions¹¹ and Project BOOST (Better Outcomes by Optimizing Safe Transitions)¹² have demonstrated the potential to reduce hospital readmission rates.^{13 14} However, implementation strategies outside of grant-funded academic environments and understanding what components of these programmes are most effective are still in development.^{15 16}

The SARS-CoV-2 pandemic further complicated transitions of care by widening existing health disparities for high-risk populations and socioeconomically disadvantaged groups. For patients reluctant to seek in-person care due to COVID, hospitals leveraged telehealth services to manage chronic disease.^17–20

Rationale

Value propositions for TCM programmes have focused on reducing hospital readmissions; however, results of these studies are unclear on the impact on readmissions from the overall programme or individual components.^{2 12 15 21–23} While many studies focus on TCM using technology for at-home surveillance, a multidisciplinary telehealth approach for TCM is not available for review in the current literature.^24–26

Specific aim

Our hospital developed a multidisciplinary telehealth-based TCM programme, coined WPH Cares, which seeks to increase access to care and services for these patients. This includes escalated assistance based on personalised needs identified after a postacute care hospitalisation. With the development of a dedicated interdisciplinary team, WPH Cares aims for a patient-centric approach, while also transmitting data back to hospital committees for quality and performance improvement. We hypothesised that successful implementation of this programme would result in decreased hospital readmissions by increasing access to care after discharge.

Methods

Context

White Plains Hospital is a 292-bed not-for-profit community hospital and member of the Montefiore Health System, located in White Plains, New York. In 2022, White Plains Hospital reported having 22 326 inpatient discharges. This report describes in detail the quality improvement (QI) intervention and integration, abiding by the reporting guidelines suggested by the Standards for Quality Improvement Reporting Excellence 2.0 guidelines.²⁷

Intervention

WPH Cares is a telehealth-based department whose mission aims to (1) provide data-driven innovative solutions to ensure patients have access to services when they need them, (2) leverage hospital and community resources to decrease 30-day hospital readmission and preventable ED utilisation, (3) improve patient access and overall healthcare experience and (4) empower patients to be proactive about monitoring and managing their health.

Established in 2018, initially as a patient experience outreach for the ED, WPH Cares has evolved into a clinical outreach programme with five integrated patient-centric units supporting the entire organisation. Each of these components is designed to screen and address barriers to care for patients during and after their transition home from the acute care setting: (1) clinical outreach, (2) access navigation, (3) diagnosis-specific care transitions, (4) clinical escalation and (5) community coordination (see figure 1).

Figure 1. Five key elements. RN, registered nurse.

Clinical outreach

Clinical outreach consisted of registered nurses (RNs) who telephonically outreach all patients discharged home from a hospital inpatient stay within 24–48 hours of discharge. WPH Cares did not contact patients discharged to a subacute rehabilitation facility, assisted-living facility, group home or hospice given the level of support already established for such patients. For those unreachable telephonically, portal messages were sent if patients had an activated patient portal account through the hospital’s electronic medical record (EMR). Structured questions focus on (1) follow-up appointments, (2) discharge instructions, (3) medication access, (4) home services/social work needs and (5) predefined questions based on discharge diagnosis (postoperative, mother-baby discharge, etc). Discrete data from these outreaches were pulled into dynamic dashboards available to leaders hospital-wide, identifying postdischarge needs of their patients.

Access navigation

Access navigation consisted of a non-clinical team of patient access associates and referral navigators who connect patients with providers and secure timely appointments. Patient access associates handled incoming calls and requests from the community to connect patients with providers within the hospital network of ambulatory practices. Referral navigators, a specialised subdivision of access navigation, prioritise patients recently discharged to ensure posthospital appointments were secured within the clinically indicated timeframe. These patients were identified through referrals from clinical teams in the hospital or internally from the clinical outreach team.

Diagnosis-specific care transitions

Advanced practice providers (APPs) and RNs prioritised patients discharged with an acute exacerbation of congestive heart failure (CHF), chronic obstructive pulmonary disease (COPD) or a primary discharge diagnosis of pneumonia (PNA). With oversight from a medical director, these teams provided an in-depth assessment of patients’ clinical status through weekly outreaches for 30 days after discharge. Tools supporting this unit included coordination with local paramedicine programme(s), integration into our ambulatory system and a vendor relationship for EMR-integrated clinical telepharmacy consultation. In addition, eligible patients with CHF were offered remote patient monitoring devices for 30 days to trend blood pressure, pulse oximetry, heart rate and daily weights; data were monitored daily by clinical staff with escalation protocols in place for abnormal readings.

Clinical escalation

The medical director along with the TCM APPs also managed clinical escalations from the clinical outreach team. Resources used to support this programme included video visits with the programme’s APPs, the hospital’s infusion centre for fluids and antibiotics, our local paramedicine programme(s) for home visits to provide urgent treatments and our hospital’s consultants for telehealth visits when indicated.

Community coordination

The community coordination team hosted weekly meetings with key stakeholders to review identified at-risk patients to coordinate resources and ensure consistent instruction is being provided to each patient across healthcare settings.

This group consisted of the Visiting Nurse Services (VNS), community paramedicine organisations, local cancer centres and ambulatory care managers, among others. WPH Cares collaborated with our own Family Health Center and other local organisations for resource sharing to reduce barriers to care, including access to charity care, transportation, palliative services, mental health and affordability of medications.

Workflow

Nurse leaders, clinical nurses, care managers and providers from all areas of the hospital were educated on the services WPH Cares offers and its overall mission and purpose. Through rounding as well as marketing materials, they instructed patients to expect a postdischarge outreach as part of discharge planning. Once patients were home from an inpatient stay, WPH Cares clinical outreach team aimed to contact them within 24–48 hours.

To support communication between ambulatory teams and community resources, the WPH Cares clinical members rounded regularly at ambulatory practices to build and maintain relationships while also holding weekly meetings with local VNS, inpatient care managers and community paramedicine programmes to coordinate messaging and resources to patients. WPH Cares also rounded weekly with inpatient teams on high-risk patients with long lengths of stay to coordinate resources needed to support a safe transition.

Study of interventions

Key process measures for this study included evaluation of 30-day readmission rates based on hospital predetermined goal setting. Run charts were used to monitor readmissions for (1) all-cause, (2) CHF, (3) COPD and (4) PNA (see figure 2). Process measure data were collected and reviewed for contact rates and contact timing related to readmissions. A logistic regression analysis was completed to determine the impact of the intervention on readmissions.

Figure 2. (1) Initiation of the WPH Cares programme as a patient experience outreach call for individuals discharged from the emergency room (December 2018), (2) focus shift to support patients and the community during the SARS-CoV-2 pandemic (March 2020), (3) redesign of WPH Cares workflow and start of intervention (May 2021), (4) formal start to diagnosis-specific transitional care management for CHF, COPD and PNA (June 2021 for CHF and COPD; October 2021 for PNA) and (5) initiation of portal messaging to patients unable to be reached telephonically (February 2022).

Measures

The primary outcome of this programme was its impact on overall 30-day readmission rates for all payors. Secondary outcomes were the impact on 30-day readmission rates for patients with CHF, COPD and PNA (Medicare only). The WPH Cares team used the hospital’s patient reporting database as a data collection tool for 30-day readmission rates. For all patients who were contacted through the clinical outreach team, process measures collected also included (1) attempt rate, (2) contact rate and (3) contact timing. Attempt rate was defined as the percentage of patients who the team tried to outreach within 10 days of discharge, regardless of outcome. The contact rate was defined as the percentage of patients who were successfully contacted telephonically within the 10-day postdischarge period. Contact timing categorises the timeframe (in hours) between the discharge time and the time of patient contact by the WPH Cares team member. Categories for contact timing include less than 24 hours, 24–48 hours, greater than 48 hours and not contacted.

Analysis

Through run charts, we compared readmission rates of the patients outreached within the 20-month study period to a 40-month prestudy period. We went back 40 months (1) to evaluate the programme intervention against a period that was before WPH Cares was originally founded, and (2) to extend our analysis prior to the SARS-CoV-2 pandemic. Five markers are identified within the run charts to show (1) initiation of WPH Cares as a patient experience outreach for individuals discharged from the ED (December 2018), (2) focus shift to support patients and the community during the SARS-CoV-2 pandemic (March 2020), (3) redesign of WPH Cares workflow and start of intervention (May 2021), (4) start to diagnosis-specific TCM for CHF, COPD (June 2021) and PNA (October 2021) and (5) initiation of portal messaging to patients not contacted telephonically (February 2022). An analysis of the run charts was completed using Shewhart control chart rules against the prestudy median line. A logistic regression analysis was completed for the 20-month study period to evaluate the impact of the WPH Cares discharge outreach on 30-day readmissions. Additionally, a χ² test of independence was used to evaluate if contact timing had an impact on 30-day hospital readmissions.

Results

Study of the WPH Cares programme ran from May 2021 to December 2022. During this time, there were 24 808 total patients who met eligibility criteria. Demographic data of those able to versus not able to be contacted are available in table 1. The median contact time was 34.25 hours. Our team attempted 98.4% (24 420) of the patients discharged and successfully contacted 68.3% (16 942) telephonically. We noted an overall improvement of 10.6% in contact rate through initiation of portal messaging in February 2022 for patients who did not pick up their phone and had an active EMR portal account. This information was unable to be distinguished between different discharge departments and is not included in table 1.

Table 1

Baseline characteristics (overall, contacted and not contacted)

Characteristic	Overall n (%)	Contacted n (%)	Not contacted n (%)	Contact rate %	P value
Total	24 808 (100)	16 942 (68.3)	7866 (31.7)
Sex					<0.001
Female	14 719 (59.3)	9931 (40.0)	4788 (19.3)	67.5
Male	10 085 (40.7)	7009 (28.3)	3076 (12.4)	69.5
Unknown	4 (0.02)	2 (0.01)	2 (0.01)	50.0
Language					<0.0001
English	22 542 (90.9)	15 558 (62.7)	6984 (28.2)	69.0
Spanish	1852 (7.5)	1104 (4.5)	748 (3.0)	59.6
Other language	414 (1.7)	280 (1.1)	134 (0.5)	67.6
Race					<0.0001
White	13 287 (53.6)	9345 (37.7)	3942 (15.9)	70.3
Black or African-American	3207 (12.9)	2144 (8.6)	1063 (4.3)	66.9
Asian, Hawaiian or Pacific Islander	665 (2.7)	444 (1.8)	221 (0.9)	66.8
American Indian	38 (0.2)	30 (0.1)	8 (0.03)	78.9
Other or unknown	7611 (30.7)	4979 (20.1)	2632 (10.6)	65.4
Ethnicity					<0.0001
Spanish/Hispanic/Latino	4032 (16)	2536 (10.2)	1496 (0.6)	62.8
Not Spanish/Hispanic/Latino	16 591 (69)	11 566 (46.6)	5025 (20.3)	69.7
Declined/unavailable/unknown	4184 (17)	2840 (11.4)	1344 (0.5)	67.9
Age					<0.0001
Mean, median, mode	59, 62, 74	60.9, 64, 74	54.8, 57, 35
Lace Score					<0.0001
Mean, median, mode	38.9, 28, 21	40, 30, 21	36, 27, 21

Readmission rates were calculated monthly and plotted over time from January 2018 to December 2022 for All Cause-All Payor, CHF-Medicare, COPD-Medicare and PNA-Medicare (see figure 2). Using Shewhart’s rules for control charts, we identified shifts and runs based on the median line of the 40-month prestudy cohort.

Within the run chart for All Cause-All Payor, there was a sustained shift of 11 consecutive points below the median line (11.0%) from September 2021 to July 2022 with an adjusted median of 9.8% for the intervention cohort.

When reviewing secondary objectives, for patients with CHF, the readmission rate run chart from January 2018 to November 2018 presents a mixed pattern with 11 consecutive points alternating across the median line (14.3%) prior to the initiation of WPH Cares. There is also a sustained shift with 12/13 data points below the median line after initiation of APP TCM intervention from August 2021 to July 2022 and an adjusted median of 9.1%.

The COPD readmission rate run chart demonstrates a small sustained shift below the median line (20.0%) from August 2019 to April 2020 with 8/9 data points below the median line prior to the study’s intervention. There is a data point outside of the upper control limits in February 2022 during the study and the median adjusted for the intervention group is 13.4%.

The PNA readmission rate run chart has a sustained shift with 8/9 data points above the median (14.9%) from April 2018 to December 2018 prior to the initiation of WPH Cares. There are no shifts or trends noted in the run chart for the intervention period. The median adjusted for the intervention is 14.0%.

A logistic regression analysis was completed to answer the question: ‘What is the likelihood of being readmitted to the hospital after an inpatient stay if there is an assessment by the WPH Cares program?’ This model controlled for age, race, ethnicity, gender, length of stay, discharge disposition location, discharge weekday, prior hospitalisations and Elixhauser comorbidity (p=0.017, OR: 8.75). Other factors that were statistically significant for increased likelihood of returning included the patient’s length of stay on index admission (p<0.0001, OR: 1.00), prior admissions (p<0.0001, OR: 1.22), prior ED visits (p=0.0001, OR: 1.06) and increased Elixhauser Comorbidity Score (p<0.0001, OR: 1.02). Factors associated with a decreased likelihood of 30-day readmission include those with a discharge disposition to home (p=0.015, OR: 6.43) and those discharged on Monday (p=0.037, OR: 8.18).

An analysis was also completed comparing readmission rates to contact timing to identify the ideal time to outreach patients after inpatient discharge. Among those in the study period, those that were contacted between 24 and 48 hours after discharge were 1.2 times less likely to be readmitted than if not contacted (254 of 3742 (6.8%) vs 647 of 7866 (8.2%); p=0.005) (see table 2).

Table 2

Contact timing analysis

Characteristic	<24 hours n=10 845	24–48 hours n=3742	>48 hours n=2355	Not contacted n=7865	P value
Sex (%)					0.025
Female	6392 (58.9)	2160 (57.7)	1379 (58.6)	4787 (60.9)
Male	4453 (41.1)	1581 (42.2)	975 (41.4)	3076 (39.1)
Unknown	0 (0)	1 (0)	1 (0)	2 (0)
Language (%)					<0.0001
English	9894 (90.8)	3415 (91.2)	2173 (92.3)	6952 (88.4)
Spanish	722 (6.7)	246 (6.5)	137 (5.8)	747 (9.5)
Other language	229 (2.1)	81 (2.2)	45 (1.9)	166 (2.1)
Race (%)					<0.0001
White	6655 (61.4)	2313 (61.8)	1406 (59.7)	4434 (56.4)
Black or African-American	1390 (12.8)	443 (11.8)	320 (13.6)	1073 (13.6)
Asian, Hawaiian or Pacific Islander	278 (2.6)	100 (2.7)	64 (2.7)	223 (2.8)
American Indian	22 (0.2)	2 (0.1)	6 (0.3)	8 (0.1)
Other or unknown	2500 (23.1)	884 (23.6)	559 (23.7)	2127 (27.0)
Ethnicity (%)					<0.0001
Spanish/Hispanic/Latino	1619 (14.9)	571 (15.2)	346 (14.6)	1496 (19.0)
Not Spanish/Hispanic/Latino	7465 (68.8)	2505 (66.9)	1596 (67.7)	5025 (63.9)
Declined/unavailable/unknown	1761 (16.2)	666 (17.7)	413 (17.5)	1344 (17.1)
Age, median (IQR)	65 (46–79)	61 (41–74)	62 (42–75)	57 (36–72)	<0.0001
Lace Score, median (IQR)	30 (21–63)	27 (21–57)	30 (21–62)	27 (21–57)	<0.0001
Readmitted in 30 days (%)	938 (8.6)	254 (6.8)	199 (8.5)	647 (8.2)	0.006
ED return in 30 days (%)	518 (4.8)	157 (4.2)	69 (2.9)	466 (5.9)	<0.0001

ED, emergency department.

Outreach survey outcomes for the study group are outlined in table 3. Of the patients assessed by the clinical outreach team, 76.6% required reinforcement of the discharge instructions. Other actions required by the clinical team included advice or education related to a medical problem or discharge diagnosis (51.5%), assistance with scheduling an appointment (21.7%), medications education (12.4%), home care or social work needs (10.2%) and pharmacy assistance (9.2%). Additionally, 3.6% of the patients assessed required assessment from the clinical escalation team.

Table 3

Outreach survey outcomes

Patient responses during telephonic outreach	n (%)	Subcategory n (%)
Total enrolled	24 808 (100)
Attempted	24 420 (98.4)
Contacted	16 942 (68.3)
Was action required by transitional care team?
Total assessed (n=13 001)
Yes	5158 (40.0)
Discharge instructions		3952 (76.6)
Advice or education about medical problem		2657 (51.5)
Scheduling follow-up		1120 (21.7)
Medication education		640 (12.4)
Home care or social work needs		527 (10.2)
Pharmacy assistance		472 (9.2)
Escalate clinical concern		185 (3.6)
No	7843 (60.3)
Follow-up appointment scheduled?
Total assessed (n=15 884)
Yes	10 545 (66.4)
No	5339 (33.6)
Did patient start taking prescribed medications?
Total assessed (n=13 661)
Yes	12 306 (90.1)
No	1355 (9.9)
Did not pick up yet and plans to		811 (59.9)
Pharmacy issue		360 (26.6)
Patient does not feel medication is necessary		108 (8.0)
Cost		28 (2.1)
Other		311 (23.0)
Questions about discharge instructions
Total assessed (n=15 889)
Yes	1552 (9.8)
Related to medications		902 (58.1)
Signs and symptoms to look out for		394 (25.4)
Postdischarge services and next steps		341 (22.0)
Wound care/incisional care		224 (14.4)
Patient did not review or does not have instructions		103 (6.6)
Other		228 (14.7)
No	14 337 (90.2)

Discussion

Summary

Our internally developed telehealth-based TCM programme in a non-academic centre demonstrated a sustained decrease in total readmission rates, as well as for patients discharged with CHF, COPD or PNA. This programme expands on the existing literature from prior studies primarily from grant-funded academic centres, which found that transitional care is correlated with fewer hospital readmissions. Our programme accomplished this through clinical outreach, improvement of access to follow-up care and addressing barriers to care.^{28 29} In addition to its telehealth base, this report also adds to existing TCM literature by providing a detailed analysis of patients in this cohort who were able to be reached by telephone based on demographic information as well as the impact of contact timing on readmission.

Interpretation

Our programme focused on postdischarge calls with the implementation of a multidisciplinary team. It has been found in previous studies that a substantial portion of patients discharged from the hospital do not remember the discharge diagnosis or discharge instructions.^{30 31} Options such as a telephone call and text message are less expensive for both provider and patient while also broadening healthcare access to patients.^{32 33} Additional benefits include a reduction in avoidable readmissions by improving patient education, early detection of barriers, enhancing communication and improving care coordination.^34–38 Prior studies support that contacting patients within 2–5 days of discharge is optimal in decreasing readmissions.^39–41 Our programme attempted 98.4% of discharges within 10 days with 68.2% of patients successfully contacted. In our cohort, we discovered that the optimal time to contact patients was between 24 and 48 hours of their discharge home from an acute care hospitalisation. This correlates with our outreach conversations where patients are more situated at home after 24 hours with a keener sense of their needs, whether clinical, access, social or medication related. There may be a population where more urgent follow-up is indicated; this is an area of future study for us.

Key challenges included coordinating care and services through numerous healthcare organisations as well as identifying the right services for the right patient. Published evidence has noted formulating holistic patient-centred instructions that address their goals and proactively detect barriers to care can address some of the most common clinical reasons patients encounter poor outcomes.^42–44 Our team found that hosting standing meetings with community stakeholders, providing transparent data as process indicators and obtaining constant feedback for process improvement were critical in building, developing and sustaining a collaborative community model. A continued challenge includes how social determinants of health impact our patients, both in the hospital and in the community.

Previous literature has found a range of community variables that are independently associated with hospital readmission.⁴⁵ Among those variables, patient demographics, particularly those who were non-Hispanic or African-American, were strongly associated with higher readmission rates.^45–47 When assessing for equity distribution, it was identified during the analysis of patient demographics that the contact rate for patients with Spanish as a primary language (59.6%) was lower compared with those who have English listed (69.0%). Patients who spoke languages other than Spanish and English were much less prevalent within our patient population, so we chose to combine them into their own category totalling 1.7% of the study population and a contact rate of 67.6%. The team also found that contact rates were lower for patients who were listed as ‘Black or African-American’ (66.9%), ‘Asian, Hawaiian or Pacific Islander’ (66.8%) or ‘Other or Unknown’ (65.4%) as compared with those listed as ‘White’ (70.3%). WPH Cares plans to use this information on disparity gaps to develop initiatives that target these underserved populations in a more effective way by working with the community these patients live in.^48–50 Our continued efforts to engage community stakeholders will be a key step in overcoming identified barriers and will be evaluated in future studies.

WPH Cares is internally funded with support from hospital leadership. The return on investment (ROI) through such a programme includes improving the overall discharge process, reducing penalties for readmissions, driving volume and loyalty for the ambulatory network and fulfilling the Centers for Medicare & Medicaid Services (CMS) criteria requirements for TCM billing in coordination with our ambulatory practices. Future work will strive towards developing a financial ROI model.

Limitations

This study is a single-centre observational programme and evaluates the workflow and processes of that institution. The results presented in this study depend on several assumptions; one of these is that the changes observed were caused by this study’s interventions rather than external factors. Making this assumption could have been avoided by including a control group, which was not feasible at our centre. As part of the QI process, we monitored as many external factors as possible and are not aware of any unforeseen influences that could have impacted the hospital readmissions. Being part of our hospital’s larger QI initiative and readmission task forces, WPH Cares was at the centre of most of the focus for readmission reduction.

Additionally, emergence of the SARS-CoV-2 pandemic posed a challenge when defining a comparable cohort for analysis, which was why a 40-month prestudy cohort was chosen for this study. Readmission rate data also included patients who were discharged initially to other facilities, hospice and group homes which do not correlate directly with the study cohort. In addition, 30.7% of our patient’s demographics are listed as ‘Other’. Our hospital is working to improve our registration process along with a campaign for improved understanding of our demographics to better serve our population and work towards more equitable access to medical care. Lastly, our hospital did not evaluate hospital readmissions to outside facilities since this was an internal QI programme focused specifically on reducing hospital readmissions to our facility.

Conclusion

We leveraged a multidisciplinary telehealth approach to improve patient engagement and access with the result of sustained decrease in 30-day hospital readmission. Future initiatives should include focused efforts on identifying disparities in access to care, bridging gaps to improve the equity of health access in our community and providing details on an ROI to encourage duplication of this process at other institutions.

The authors acknowledge White Plains Hospital President & CEO, Susan Fox; EVP, Patient Care Services and Chief Nursing Officer, Leigh Anne McMahon, DNP, MHA, RN, NEA-BC; Chief Quality Officer, Rafael Torres, MD, FACEP; EVP and Chief Medical Officer, Michael Palumbo, MD, FACP; EVP, Ambulatory & Physician Services, Frances Bordoni; and the leadership team at White Plains Hospital for their support in developing the WPH Cares programme. We also thank the University of Pennsylvania (UPENN) and Project Red in Boston, Massachusetts, for their previous research in this area and their willingness to share information with our team as we developed the WPH Cares programme. Additionally, we thank the entire WPH Cares team for their tireless dedication to outreaching and supporting our patient population and the various teams throughout the hospital who have provided support and guidance for this programme. We thank all the various programmes that continue to collaborate with WPH Cares to support our patients including Empress Paramedicine, Scarsdale Volunteer Ambulance Corps, Life365, Visiting Nurse Services of New York, Visiting Nurse Services of Westchester, the Family Health Center and Cureatr Clinic, Inc.

Data availability statement

Data are available upon reasonable request. Data for this study may be made available as an R-Markdown file upon reasonable request.

Ethics statements

Patient consent for publication

Not applicable.

Ethics approval

This study was exempt from review by the White Plains Hospital Institutional Review Board and was not subject to full review based on its qualification as an ongoing QI initiative.

Footnote

Contributors ME and FNJ conceived the presented idea and developed the QI study design. RCSF conducted background research for the study. JS and ME performed computations and conducted the analysis. ME, RCSF and FNJ wrote the first draft of the manuscript. ME, RCSF, FNJ and PH contributed to the final version of the written manuscript. ME is the guarantor of this study.

Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

Competing interests None declared.

Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

Provenance and peer review Not commissioned; externally peer reviewed.

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