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Research Article| Volume 20, 101236, March 2023

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Can training over phone calls help improve outcomes for COVID-19 positive patients under home isolation? An analysis of the COVID-19 Care Companion Program in Punjab, India

Open AccessPublished:January 26, 2023DOI:https://doi.org/10.1016/j.cegh.2023.101236

      Abstract

      Background

      Phone-supported recovery of COVID-19 patients in home isolation could be an effective way of addressing COVID-19 in contexts with limited resources. The COVID-19 Care Companion Program (CCP) is one such intervention, designed to support patients and their caregivers in remote, evidence-based management of COVID-19 symptoms.

      Objective

      To estimate the effect of providing phone-based training to COVID-19 patients and their caregivers on the likelihood of hospitalizations and mortality.

      Methods

      A pragmatic randomized trial was conducted to assess the effect of a novel phone-based training program on COVID-19 home-isolated patient outcomes. The analysis compared the outcomes of death and hospitalizations in the teletraining intervention group (CCP) to those receiving standard of care (SoC).

      Results

      Logistic regression models adjusted for age, gender, education, occupation, and poverty, as measured by family possession of Below Poverty Line (BPL) card, were used to look at the effect of intervention on hospitalization and mortality. While the CCP intervention had no effect on 21-day mortality (OR 0.64; 95% CI, 0.19 to 2.12), it was associated with a 48% reduction in 21-day hospitalization (OR 0.52; 95% CI, 0.31 to 0.90).

      Conclusion

      COVID-19 CCP teletraining intervention reduced the rate of hospitalization, potentially reducing the burden on hospitals.

      Keywords

      1. Introduction

      COVID-19 is reported to have infected over 383 million people globally and claimed over 5.6 million lives.
      There is large regional heterogeneity in the manifestation of COVID-19 complications, with most patients (∼40%) having only mild or moderate symptoms of the disease. In China, for instance, approximately only 15% required oxygen support, while 5% manifested complications such as respiratory failure, acute respiratory distress syndrome, sepsis and septic shock.
      The novel coronavirus pneumonia emergency response epidemiology team: vital Surveillances: the epidemiological characteristics of an outbreak of 2019 Novel Coronavirus diseases (COVID-19)-China 2020.
      In India, a majority of COVID-19 patients appeared to be either mildly symptomatic or asymptomatic and required minimal intervention during recovery. Such a scenario lends itself well to interventions that support home management of symptoms, with evidence-based medical guidance and monitoring.

      Government of India Ministry of Health & Family Welfare Revised Guidelines for Home Isolation of Mild/asymptomatic COVID-19.

      Such patients are well suited for recovery at home, when supported with high-quality evidence-based medical recommendations, potentially leading to the judicious utilization of limited health infrastructure.
      World Health Organization Website
      COVID-19 strategy update.
      Studies on isolation and management particularly in low and middle-income countries (LMICs), are few. One such study was conducted in Chennai, India and examined the difference between COVID-19 Care Centers (CCC) and isolation facilities/hospitals as centers for monitoring asymptomatic and mildly symptomatic COVID-19 patients. A majority of patients within CCCs reported rapid and uncomplicated recovery.
      • Krishnasamy N.
      • Natarajan M.
      • Ramachandran A.
      • et al.
      Clinical outcomes among asymptomatic or mildly symptomatic COVID-19 patients in an isolation facility in Chennai, India.

      1.1 Program description

      The Care Companion Program (CCP) is designed to equip patients and caregivers with the skills needed to support a patient's recovery. The program is currently running in 327 Government health facilities in six states of India and has reached over a million patients and caregivers. This intervention has demonstrated efficacy across different conditions, showing a reduction in post-surgical cardiac complications by 71%,
      • Liu J.
      • Alam S.S.
      • Guhabiswas R.
      • et al.
      Impact of a family caregiver training program in Kolkata, India on post-operative health perceptions and outcomes of cardiothoracic surgical patients.
      maternal complications by 12%, newborn complications by 16% and newborn readmissions by 56%.
      • Kashyap S.
      • Spielman A.F.
      • Ramnarayan N.
      • et al.
      alImpact of family-centred postnatal training on maternal and neonatal health and care practices in district hospitals in two states in India: a pre–post studyBMJ Open.
      COVID-19 precautions and restrictions necessitated a telephonic method of deploying the CCP.
      There is a gap in evidence describing the effectiveness of home isolation interventions for COVID-19, supported by the teletraining of caregivers. Therefore, the effect of CCP on hospitalizations and mortality merits examination.

      2. Methods

      2.1 Study design

      The participants for the study were identified from a list of COVID-19 patients obtained from the Punjab State government. Using simple random sampling, patients eligible for home isolation were recruited into the study. The data was shared through a secure mechanism, maintaining privacy and confidentiality.
      The prevailing dynamic lockdown conditions during the conduct of the study permitted only telephonic patient/investigator interactions, which necessitated the application of pragmatic randomized controlled trial methods.
      Patients were randomly allocated to either the CCP group, receiving teletraining for home isolation, or the standard-of-care group (here, referred to as SoC), where participants did not receive teletraining support for COVID isolation, but were exposed to miscellaneous private or government health messages.
      Patients were allocated to either the CCP or SoC group in a 3:1 ratio, in order to ensure that a greater number of patients could be covered under the intervention. The intervention was in the form of a single phone-based training session, pertaining to topics such as caregiver precautions, management of symptoms, the recognition of danger signs in a patient, and when to seek hospital care.

      2.2 Inclusion and exclusion criteria

      Consenting adult caregivers of patients who had tested positive for COVID-19, under home isolation were considered eligible for the study. Conditions for disqualification from the study included caregiver and/or patient being too sick to respond to the survey, change in isolation status (i.e. patient having to shift from home isolation to a hospital), or a mismatch in contact information.

      2.3 Participant recruitment and study timeline

      Eligible and consenting individuals participated in an initial survey over the phone. The study questionnaire captured socio-demographic details along with baseline COVID-19 knowledge. Subsequently, those in the intervention group received the intervention in the form of teletraining.
      After a gap of 21 days, a follow up survey was conducted to assess the outcomes in the CCP and SoC groups. Oral consent for the teletraining and all the interviews was obtained and recorded. Ethical clearance for the study was obtained from ACE Independent Ethics Committee (DCGI Reg. No. ECR/141/Indt/KA/2013).

      2.4 Outcomes

      Outcomes of hospitalizations and deaths at the end of 21 days, as reported by the family members were compared between CCP and SoC groups. A logistic regression model adjusted for age, gender, education, occupation, and poverty was used to assess the likelihood of hospitalization and mortality with teletraining.

      2.5 Statistical analyses

      All analyses were performed on STATA 16.
      StataCorp
      A retrospective power calculation was done to determine the power of the study. In the absence of literature, a baseline difference of 3% in the risk of hospitalization between the CCP and SoC group was used to guide power calculations. With 763 patients in the CCP group and 592 in the SoC group, the study was estimated to have a power of 74.7% in detecting a 3% difference in the risk of hospitalization. This study describes the preliminary results of a per-protocol analysis.

      3. Results

      There was a low overall response rate owing to factors such as incorrect contact information, patients having subscribed to ‘Do Not Disturb’ services, phones being unreachable or switched off (Table 1).
      Overall, 45.1% from SoC and 42.8% of those allotted to CCP groups were contacted. Among those contacted and eligible in the SoC group, 85.4% consented and completed the initial survey. Among those contacted and eligible in the CCP group, 52.3% consented, completed the training and finished the initial survey (Fig. 1).
      Fig. 1
      Fig. 1Flowchart of participants
      *SoC= Standard of Care; †CCP=Care Companion Program.
      As of May 2021, 49.5% and 37.8% patients among those who completed initial surveys, were contacted. In the group contacted at this stage, the response rates were 65.2% for the SoC and 54.6% for the CCP group. Among those contacted, a follow-up survey was completed for 85.4% and 83.2% groups in SoC and CCP groups respectively (Fig. 1).

      3.1 Patient demographics for the initial survey

      A statistically significant larger number of participants in the CCP group were employed and more likely to be characterized as ‘poor,’ as compared to the SoC (see Table 2). This statistically significant difference between the CCP and SoC groups in terms of the number of individuals employed, translated to a modest difference of 2% and similarly the difference in the proportion of individuals meeting the criteria for poverty between the CCP and SoC groups, was found to be 3%. The largest proportion of participants (nearly 57.38%) belonged to the 18–44 age group of the CCP group. Males outnumbered females in both the groups (63.05% and 62.59% in SoC vs CCP group respectively), but the difference was not statistically significant.
      Table 1Reasons for not being to establish initial contact and ineligibility.
      Reasons for no contactSoC
      SoC = Standard of Care.
      (N = 3055) (54.8%)
      CCP
      CCP = Care Companion Program.
      (N = 11263) (56.9%)
      Call connected but never picked up31%39.7%
      Call did not connect (Switched off/out of coverage/not reachable)29.2%24.5%
      Call was picked but receiver disconnected immediately23.4%16.5%
      Number invalid/incomplete7.5%6.4%
      Patient hospitalized3.1%3.5%
      Other reasons5.5%9.1%
      a SoC = Standard of Care.
      b CCP = Care Companion Program.
      Table 2Patient Demographics for the Initial, Loss-to-follow up and Follow up survey.
      Initial SurveyLoss to follow upFollow up Survey
      VariableSoC
      SoC = Standard of Care, completed presurvey.
      (N = 2146) N (%)
      CCP
      CCP = COVID-19 Care Companion Program, completed teletraining and presurvey.
      (N = 4429) N (%)
      p
      p-value from Chi-square test of independence between groups.
      SoC
      SoC = Standard of Care, completed presurvey.
      (N = 470) N(%)
      CCP
      CCP = COVID-19 Care Companion Program, completed teletraining and presurvey.
      (N = 912) N (%)
      p
      p-value from Chi-square test of independence between groups.
      SoC
      SoC = Standard of Care, completed presurvey.
      (N = 592) N(%)
      CCP
      CCP = COVID-19 Care Companion Program, completed teletraining and presurvey.
      (N = 763) N (%)
      p
      p-value from Chi-square test of independence between groups.
      Patient age group
      <18147 (6.8%)270 (6.1%)0.04535 (7.4%)84 (9.2%)0.67739 (6.5%)55 (7.2%)0.255
      18–441153 (53.7%)2539 (57.3%)256 (54.4%)492 (54%)291 (49.1%)409 (53.6%)
      45–60566 (26.3%)1091 (24.6%)123 (26.1%)236 (25.9%)173 (29.2%)206 (27%)
      >60280 (13%)525 (11.8%)56 (11.9%)98 (10.7%)89 (15.0%)93 (12.9%)
      Gender
      Male1353 (63%)2772 (62.5%)0.738300 (63.8%)573 (62.8%)0.715395 (66.7%)488 (63.9%)0.289
      Female793 (36.9%)1656 (37.3%)170 (36.1%)339 (37.1%)197 (33.2%)275 (36.0%)
      Education
      No education45 (2.1%)105 (2.37%)0.6815 (3.21%)20 (2.25%)0.3058 (1.36%)15 (1.99%)0.039
      Some Schooling (Primary to 12th)934 (43.5%)1950 (44.1%)197 (42%)350 (39.3%)246 (41.6%)264 (35.1%)
      Graduation/PG1166 (54.3%)2367 (55.5%)256 (54.7%)519 (58.3%)336 (56.9%)473 (62.9%)
      Occupation
      Unemployed or Homemaker514 (23.9%)1073 (24.2%)0.001114 (24.3%)219 (24.5%)0.39130 (22%)168 (22.2%)0.783
      Employed1444 (67.3%)3080 (69.5%)308 (65.6%)602 (67.5%)406 (68.8%)526 (69.6%)
      Other186 (8.6%)273 (6.1%)47 (10%)70 (7.8%)54 (9.1%)61 (8%)
      Poverty as measured by BPL
      Below Poverty Line.
      card ownership
      No1741 (81.2%)3494 (79%)0.011374 (79.9%)697 (78.4%)0.366493 (83.7%)605 (80.2%)0.251
      Yes336 (15.6%)817 (18.4%)73 (15.6%)161 (18.1%)83 (14%)131 (17.3%)
      Don't know65 (3%)109 (2.4%)21 (4.4%)31 (3.4%)13 (2.2%)18 (2.3%)
      a SoC = Standard of Care, completed presurvey.
      b CCP = COVID-19 Care Companion Program, completed teletraining and presurvey.
      c Below Poverty Line.
      d p-value from Chi-square test of independence between groups.

      3.2 Patient demographics for the loss to follow up survey

      There were no significant differences between the patients’ socio-demographic characteristics such as age, gender, occupation, and poverty between the two groups in the loss to follow-up population (see Table 2).

      3.3 Patient demographics for the follow up survey

      There was a significant difference in education status indicators between SoC and CCP groups in the follow up survey with 62.9% of participants in the CCP group being college graduates, as compared to 56.9% of participants in the SoC group (Table 2). A greater number of individuals in the CCP group reported having no education. This should be interpreted conservatively due to the small number of participants in these subgroups. Differences with respect to age and gender were not statistically significant.
      Table 3 presents differences in patient outcomes by CCP and SoC allocation. Odds ratios (OR) along with 95% confidence intervals (CI) and p-values are reported for both unadjusted and adjusted models. All models are adjusted for age, gender, education, occupation, and poverty.
      Table 3Risk of death (Model 1) and hospitalization (Model 2) in CCP versus SoC.
      SoC
      SoC = Standard of Care.
      (Control) N (%)
      CCP
      CCP = COVID-19 Care Companion Program.
      (Intervention) N (%)
      Unadjusted Odds Ratio (95% CI
      CI = Confidence Interval §Adjusted for age, gender, education, occupation and poverty.
      )
      Unadjusted Odds Ratio (95% CI
      CI = Confidence Interval §Adjusted for age, gender, education, occupation and poverty.
      )
      Deaths
      Total592 (43.69%)763 (56.31%)
      Death (N = 12)7 (58.33%)5 (41.67%)0.55 (0.17, 1.45); p = 0.3110.64 (0.19, 2.12); p = 0.51
      Any hospitalization, excluding deaths.
      Total
      Adjusted Odds ratio for death used 1355 observations with values available for confounders, and 1343 for hospitalization p = P-value.
      585 (43.56%)758 (56.44%)
      Hospitalization (N = 60)36 (60%)24(40%)0.50 (0.29, 0.85); p = 0.0100.52 (0.31, 0.90); p = 0.016
      a SoC = Standard of Care.
      b CCP = COVID-19 Care Companion Program.
      c CI = Confidence Interval §Adjusted for age, gender, education, occupation and poverty.
      d Adjusted Odds ratio for death used 1355 observations with values available for confounders, and 1343 for hospitalization p = P-value.
      The adjusted model for mortality with 1327 observations, indicated 36% lower likelihood of mortality in the CCP group as compared to the SoC group. However, this was not found to be statistically significant (OR, 0.64; 95% CI, 0.19 to 2.12; p < 0.63).
      The second model compared hospitalizations in patients under home isolation, excluding deaths, and indicated a 48% lower likelihood of hospitalization in the CCP group as compared to the SoC group. The finding was significant (OR, 0.52; 95% CI, 0.31 to 0.90; P = 0.016).

      4. Discussion

      This study found a 48% reduction in 21-day hospitalizations among its participants. These findings signal the potential role of remote, phone-based training/remote engagement and support strategies in reducing the strain on overburdened health facilities through the judicious utilization of limited resources and infrastructure.
      Loss to follow up was a persistent limitation during different phases of this study, with a majority of patients unreachable by telephone. Insights into the reasons for the loss to follow up could help in strengthening crucial programmatic elements for scaling remote interventions. Alternative outreach methods for patients and caregivers could include popular, mainstream messaging services such as WhatsApp.
      No evidence pertaining to the effect of CCP intervention on reduced mortality was found. However, this could be due to the study in its current stage being underpowered to detect the effect size of the intervention (there was a total of 12 deaths in the sample).
      Given how the participants of the study were patients isolating at home, the low overall mortality rate could be attributable to the study sample comprising largely milder, uncomplicated cases. Indeed, the death rate reported from this study in the SoC group was 1.18% and the COVID-19 CCP was 0.66%.
      The nuances of design and implementation in this study align well with others assessing the suitability and preference for home-based care among mild/asymptomatic COVID-19 patients.
      • Murarkar S.
      • Mahajan S.
      • Gothankar J.
      The symptoms and CO-morbidities of COVID-19 patients at home isolation in India.
      In Telangana, 94% positive patients in a government primary health center, reported mild symptoms and opted for home isolation. Similarly, a study by Bhardwaj et al. reported a better quality of life among mildly symptomatic or asymptomatic patients under home isolation, when compared with patients under facility isolation.
      • Bhardwaj P.
      • Joshi N.K.
      • Gupta M.K.
      • et al.
      Analysis of facility and home isolation strategies in COVID 19 pandemic: evidences from Jodhpur, India [published correction appears in infect drug resist. 2021 Jul 02;14:2555].
      Patients under home isolation reported greater ease in performing daily activities and reported lower anxiety.
      • Samsuddin M.F.
      • Karim J.
      • Salim A.A.
      The outcomes of health education programme on stress level among the caregivers of post total knee replacement surgery.
      As per a cross-sectional study conducted in a tertiary hospital at Pune, Maharashtra, India, 51% of the patients registered themselves for home isolation on the day they tested positive, providing strong evidence of patients’ preference for home-based isolation.
      • Murarkar S.
      • Mahajan S.
      • Gothankar J.
      The symptoms and CO-morbidities of COVID-19 patients at home isolation in India.
      Even outside the context of COVID-19, phone-based dissemination of health information has been crucial to facilitating equitable access to health information, providing greater agency to patients in their healthcare journey and relieving pressure on acute care services.
      • Phillips J.L.
      • Davidson P.M.
      • Newton P.J.
      • Digiacomo M.
      Supporting patients and their caregivers after-hours at the end of life: the role of telephone support.
      Several studies have established the integral role phone-based interventions play in supporting patients and their caregivers through conditions such as cancers, mental health disorders and cardiovascular conditions, resulting in substantial improvements in patient and caregiver experiences, increases in regular follow-ups, reductions in episodes of emergency hospital visits and a reduction in the likelihood of caregivers developing depression.
      • Dobkin R.D.
      • Menza M.
      • Allen L.A.
      • et al.
      Telephone-based cognitive–behavioral therapy for depression in Parkinson disease.
      • Possin K.L.
      • Merrilees J.J.
      • Dulaney S.
      • et al.
      Effect of collaborative dementia care via telephone and internet on quality of life, caregiver well-being, and health care use: the care ecosystem randomized clinical trial.
      • Bakas Tamilyn
      • Farran Carol J.
      • Austin Joan K.
      • Given Barbara A.
      • Johnson Elizabeth A.
      • Williams Linda S.
      Stroke caregiver outcomes from the telephone assessment and skill-building kit (TASK).
      • Ghorbani F.
      • Zare M.
      • Heshmati Nabavi F.
      • Behnam Vashani H.
      • Bari A.
      Effect of education and telephone counseling on caregiver strain and unmet needs in family caregivers and self-care behaviors in patients with cancer: a randomized clinical trial.
      • Nasiriani K.
      • Motevasselian M.
      • Farnia F.
      • Shiryazdi S.M.
      • Khodayarian M.
      The effect of telephone counseling and education on breast cancer screening in family caregivers of breast cancer patients.
      • Feeney Mahoney Diane
      • Tarlow Barbara J.
      • Jones Richard N.
      Effects of an automated telephone support system on caregiver burden and anxiety: findings from the REACH for TLC intervention study.
      • Bakas T.
      • Austin J.K.
      • Habermann B.
      • et al.
      Telephone assessment and skill-building kit for stroke caregivers: a randomized controlled clinical trial.
      However, elements such as declining participation also observed in this study, especially over subsequent follow up calls need to be addressed. It is plausible that this decline could be attributed to a reluctance in engaging with interviewers over multiple calls, the possibility of either complete recovery or further deterioration in patient's conditions rendering them unable/disinvested to engage with interviewers.

      4.1 Strengths and limitations

      This study evaluates the impact of phone-based training for patients and caregivers during a modern public health crisis of unprecedented magnitude.
      The strengths of the study include the application of a rigorous randomized controlled trial design. Additionally, the study also benefited from being conducted telephonically increasing its safety and scalability. The use of objective outcome measures such as deaths and hospitalizations did not allow for reporting biases. Some of the major limitations of the study include initial non-response and loss to follow-up, possibly due to participation fatigue and that the quality metrics pertaining to the adoption of CCP could not be reported at the current stage of the study.

      5. Conclusion

      The findings from this study suggest that the COVID-19 CCP teletraining intervention could effectively reduce the likelihood of hospitalization among COVID-19 home isolated patients. This intervention, having harnessed the competence of family caregivers in the home-based management of uncomplicated infections, has provided valuable insight into the effectiveness of providing training and agency to a potentially unexplored, high-value resource in extending the continuum of healthcare. Remote teletraining of caregivers, can be an effective strategy for health systems to use in this pandemic and other crisis situations for reducing the burden on healthcare resources.

      Sources of 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.

      Declaration or conflict of interest

      The authors do not have any conflicts of interest to declare.

      CRediT authorship contribution statement

      Seema Murthy: Conceptualization, Methodology, Writing – original draft, Writing – review & editing. Adithi Chandrasekar: Software, Data cleaning and management, Writing – original draft, Writing – review & editing. Shirley D. Yan: Writing – review & editing. Nikkil Sudharsanan: Writing – review & editing. Rashmi Pant: Formal analysis, and, Data, Visualization, Writing – review & editing. Arjun Rangarajan: Writing – review & editing. Navya Mishra: Writing – review & editing. Divya Mishra: Project administration, Writing – review & editing. Huma Sulaiman: Project administration, Writing – review & editing. Baljit Kaur: Writing – review & editing. Shahed Alam: Writing – review & editing.

      Acknowledgments

      We are grateful to Mr. Pradeep Kumar and the teletraining team for their timely coordination of the data and for sharing their insights with patients during the study.

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