ABSTRACT
Current evidence indicates that the benefits of tele-health may not be uniform across all patients. Therefore, to understand what specific variables influence use of home-based telemanagement in COPD, we conducted this retrospective study.
A 6-month home-based telemanagement program (HTP) was offered to 1,074 COPD patients over a 4-year period. Multivarible linear regression analysis was used to identify predictors of HTP use/week (phone calls and specialist consultations) among all variables: clinical (body mass index, co-morbidities, HTP prescription not following an exacerbation, long-term oxygen therapy use, COPD severity, hospital readmissions, exacerbations and death), socio-demographic (sex, age, place of abode), smoking history, arterial blood gases (ABG), and specialist/general practitioner (GP) urgent need. Logistic regression was conducted to predict relapses/hospitalizations risk as well as the disease impact (COPD Assessment Test, CAT) at the end of the program.
Presence of relapses (p < 0.001), ABGs (p < 0.001) and GP request (p < 0.001) were significantly associated with higher HTP-use. Smoking history (OR 1.542 [IC 95% 1.069-2.217], p = 0.020), specialist (OR 2.895 [2.144–3.910], p < 0.001) and GP consultations (OR 6.575 [4.521–9.561], p < 0.001) were the only independent risk factors for relapse. No predictor of hospitalization was found. High final CAT score was inversely related to oxygen therapy use (p = 0.001) and HTP prescription (p < 0.001), and positively related to presence of co-morbidities (p = 0.001) and baseline CAT (p < 0.001).
This HTP in Lombardy shows that relapsers, people requiring several ABGs and urgent GP visits are the patient subgroup most likely to consume telemanagement services (scheduled and unscheduled). We propose a patient ‘identikit’ to improve prioritization for HTP prescriptions.
Abbreviations
| ABG | = | arterial blood gases |
| AUC | = | under the curve |
| BMI | = | body mass index |
| CAT | = | COPD Assessment Test |
| COPD | = | Chronic obstructive pulmonary disease |
| FEV1 | = | forced expiratory volume in 1 sec, |
| FiO2 | = | inspiratory fraction of oxygen |
| FVC | = | forced vital capacity |
| GP | = | general practitioner |
| HTP | = | home-based telemanagement program |
| ICT | = | information communication technologies |
| LTOT | = | long-term oxygen therapy |
| SaO2 | = | oxygen arterial saturimetric percentage |
Introduction
Chronic obstructive pulmonary disease (COPD) is one of the most high-cost chronic diseases in the developed world (Citation1). Recent increases in healthcare costs, mainly due to in-hospital treatments, have highlighted the need for new management strategies (structured telephone support, or telemanagement) for these patients (Citation2). Modern information communication technologies (ICT) offer new options to deliver remote specialized healthcare, and in the last decade several studies focusing on the effects of various telemanagement programs for patients with COPD have been published (Citation3–16).
The benefits of a home-based telemanagement program (HTP) have yet to be fully demonstrated, and we are still far from being able to propose a large-scale routine use of HTPs. Positive results were found for some HTPs (featuring, in particular, constant analytical and decision-making support by nurses and doctors with full therapeutic authority 24 h/day) compared to controls in terms of hospital admissions (Citation3,Citation7,Citation12,Citation14), healthcare resources utilization (Citation8–10,Citation12,Citation15), quality of life (Citation5), cost savings (Citation3,Citation10,Citation14), and mortality (Citation15). But no advantages were found in others concerning the number of COPD admissions (Citation13,Citation16), quality of life/psychological outcomes (Citation4), and mortality (Citation5,Citation14,Citation16). These conflicting results could be accounted for, at least in part, by the fact that the literature to date on home-based telemanagement in patients with COPD consists mainly of single-center experiences carried out in small patient cohorts with different methodologies, levels of disease severity, settings, instrumentations, rationales, resources and definitions of control group (i.e., usual care) (Citation2).
Tailored, flexible and locally responsive services could be important factors for the successful implementation of cross-border telemedicine services (Citation17). For these reasons the “one glove fits all” approach seems too simplistic for a heterogeneous population such as patients with COPD (Citation18). Unfortunately, decision-makers, e.g. the healthcare authorities, are rushing to introduce HTPs in response to the pressure to reduce hospitalizations among patients with COPD (Citation19). As the effects of tele-health may not be uniform across all patients, research is needed to identify subgroups of patients for whom tele-health is either particularly beneficial or harmful (Citation4,5). At the same time no real-life studies exist focusing on how patients’ clinical, behavioural and sociodemographic conditions may influence use of a telemanagement program.
Our home-based telemanagement program was adopted in the Lombardy Region in 2004 and has since then undergone extensive testing and improvement (Citation20,21). A systematic data collection procedure was designed to assess the organizational impact and level of services performed of the proposed HTP. Drawing on this large database, the present retrospective study aimed to clarify if and how the clinical, geographic, behavioural and demographic characteristics may have influence on patients with COPD their weekly HTP use. As secondary aims, we aimed to identify from among patients’ clinical, geographic, behavioural and demographic characteristics those variables that may predict relapses, hospitalizations and level of disease impact at the end of the program.
Methods
Study subjects
HTP operates within a 24-hospital network authorized by the Lombardy Region operating as part of the Public Health Service without cost for patients. Patients of both genders living in the Lombardy Region with confirmed spirometry diagnosis of COPD according to ATS guidelines (Citation22) aged >18 years, and with at least one hospitalization or 2 severe relapses for acute COPD in the previous 6 months were eligible for enrolment in the HTP. Exclusion criteria included use of mechanical ventilation, illness with poor prognosis, cognitive impairment, or hospital inpatient admission at the time of patient selection.
Access to the HTP could be suggested by the attending pulmonologist or the general practitioner (GP) at the time of hospital discharge or after a visit to the outpatient clinic. Before enrollment in the program all patients were clinically stable for 10 days.
Study design
At baseline, a complete medical history (symptoms, smoking history), spirometry data (forced expiratory volume in 1 second [FEV1] %pred, forced vital capacity [FVC] %pred, FEV1/FVC), anthropometric data (age, gender), body mass index (BMI), nocturnal saturimetry tracing (mean nocturnal SaO2/FiO2), number and type of co-morbidities (based on the hospital discharge report or GP database), long-term oxygen therapy (LTOT) use, and prescribed medications were collected. At the beginning and end of the HTP, patients underwent in-hospital physical examination, arterial blood gases (ABG) measurement and the COPD Assessment Test (CAT) to assess the disease impact (Citation23). All patients and their GPs signed the informed consent form.
The program consisted of a structured physician-directed, nurse-managed telephone support service added to telemonitoring. A dedicated hospital nurse-tutor, available from 8:00 am to 4:00 pm weekdays, was the key figure who liaised between hospital personnel (doctors, nurses, physiotherapist) and the patient's home (i.e., patient, caregivers and GP) by telephone. Details of the program have been described elsewhere (Citation3). In brief, our approach consisted of scheduled telephone calls on a weekly basis as well as unscheduled calls (for urgent need) as required by the patient when they experienced some signs and symptoms. The patient was supplied with a pulse oximeter (GIMA© pulsed oxymeter; Gima S.p.A., Gessate, MI, Italy).
The program was proposed for 6 months but could be renewed for a further 6 months if patients were still unstable (defined as need for change in medications or unstable diurnal or nocturnal pulsed saturation in the last 15 days), had not reached adequate self-management of disease medications or oxygen use, if their disability level had worsened (increase in dysponea during activities of daily life) or if there were family/caregiver unresolved issues (appearance of social, organizational problems or serious care-related burden or stress). Three telemedicine service providers supported the 24 hospitals, providing biomedical devices and call centre activities, managing the clinical database and offering clinical and nursing services during the night and weekends. HTP costs were reimbursed by the National Health system for a total of €720.00/patient for the 6-month period. The renewed HTP program for a further 6 months was reimbursed for the sum of € 480.00 per patient.
Our retrospective analysis covered a total of 282 months (range 6–1120 months) of HTP services offered to 1,074 consecutive patients with COPD according to their clinical needs. Data retrieved from patients’ records included: geographical location of residence (urban vs. rural, defined as > 5,000 vs. ≤ 5,000 inhabitants), reasons for HTP prescription (post COPD hospitalization vs. in a stable state), program interruptions and cause of early program failures (death, drop-out, unscheduled hospital admission) and relapses without hospital admission, HTP use (scheduled/unscheduled phone calls and number of consultations required of the pulmonologist, ABGs, and unscheduled GP urgent home visits). The time spent on the HTP being different for each patient, HTP use was normalized on a “per week” basis (HTP/w) (i.e., total number of scheduled calls, unscheduled calls and pulmonologist consultations required /number of patient's follow-up weeks).
Statistical analysis
Continuous variables are expressed as mean ± SD; categorical variables are expressed as number of cases (%). Statistical analyses were performed using IBM SPSS Statistics Version 22. Normal distribution was checked with the Kolmogorov–Smirnov test. P-values = 0.05 were considered as statistically significant. To check the associations between patients’ clinical, geographic, behavioural and demographic characteristics and the HTP/w, presence of relapses/hospitalizations and CAT score at the end of the pathway, univariate and multivariable linear regression analyses were performed.
For HTP/w and CAT score, Pearson's correlations were used among the independent continuous variables; for the multivariable linear regression analysis, the stepwise method for the selection of the variables was chosen. This procedure was conducted using the “probability-of-F-to-enter ≤ 0.050” and the “probability-of-F-to-remove ≥ 0.100”.
A stepwise method was performed to identify significant variables associated with relapse/hospitalization. This procedure uses a forward selection with “a p-value to exclude” of 0.10 and a “p to enter” of 0.05. Only the resulting model is here reported; the goodness of fit was tested with the Hosmer–Lemeshow (H–L) test. Receiver operating characteristic (ROC) curves were used to highlight the true-positive rate (sensitivity) and the false-positive rate (1-specificity) at various levels of the exacerbation or hospitalization risk.
Results
Patients enrolled during the 4 years of activity, subdivided by hospital and regional district, are reported in . Baseline characteristics of the study population are shown in .
Table 1. Baseline characteristics of study population.
Figure 1. Number of patients enrolled (2010–2013) per hospital and district of Lombardy Region. Legends: BG = Bergamo; BS = Brescia; Co = Como; CR = Cremona; LC = Lecco; LO= Lodi; MN = Mantova; MI = Milano; MO = Monza; PV = Pavia; SO = Sondrio; VA = Varese.
A total of 842 patients (78.4%) completed the HTP program. The causes of HTP interruption for the remaining 232 patients (21.6%) were: death for COPD (n = 14), death for other causes (n = 35), drop-out (n = 43), start of invasive ventilation (n = 2), new prevailing disease (n = 1), hospitalization for COPD (n = 84), and hospitalization for other causes (n = 43).
Higher HTP/w was significantly associated with ABG need (b-coefficient = 0.738; p < 0.001), relapses (b-coefficient = 1.747; p < 0.001) and GP consultations (b-coefficient = 2.777; p < 0.001) (). These variables accounted for 34.2% of the variance in HTP/w.
Table 2. Univariate and multivariable linear regression analyses for HTP use.
HTP/w (0.83 ± 3.06 vs. 0.71 ± 0.64; p < 0.001), ABGs requested (0.08 ± 0.09 vs. 0.07 ± 0.02; p = 0.001) and GP visits (0.03 ± 0.10 vs. 0.00 ± 0.03; p < 0.001) were significantly higher in relapsers than non relapsers. Of the 1074 patients, 399 (37%) presented 896 relapses without hospitalization; 495/1074 (46%) remained free from exacerbation and hospitalization, while 180 patients (16.8%) were both hospitalized and exacerbated. The risk to have a relapse was significantly higher for the group of smokers/ex-smokers than for non-smokers, and around three times higher for patients who required a consultation with the specialist than for those who did not, and around 6.5 times higher for patients who needed contact with the GP vs. those who did not need it ().
Table 3. Variables associated with relapse at multivariable analysis.
The model correctly predicted these causes as a risk for relapse with an accuracy of 72.9%. Of the 611 patients without relapse, the model correctly identified 564 of them (92.3%) as not likely to have one. Similarly, of the 364 patients who actually relapsed, the model correctly identified 147 (40.4%) as likely to have one. Considering the ROC curve, the area under the curve (AUC) was 0.745 (95% confidence interval [CI] 0.713–0.777), indicating that the model was moderately accurate.
Out of 1074 patients, 683 (64%) presented no hospitalizations during the HTP program, while 87 patients had at least one hospitalization for COPD and 304 patients were hospitalized for causes not related to COPD. In the multivariable logistic model, no variables were sufficiently strong to predict hospitalization risk.
A high CAT final score (high disease impact) was significantly associated with amount of co-morbidity (b-coefficient = 3.561, p = 0.001) and CAT baseline score (b-coefficient = 0.558, p < 0.001) while it was inversely associated with oxygen therapy prescription/use (b-coefficient = -1.866, p = 0.001) and HTP prescription when patients were in stable state (i.e., not following exacerbation) (b-coefficient = -2.606; p < 0.001) (). The variables were able to account for 41.3% of the variance in CAT score at the end of the pathway.
Table 4. Univariate and multivariable linear regression analyses for CAT score at the end of the pathway.
Discussion
The present study has shown that during the course of a 6-month home-based telemedicine program, all patients with COPD required weekly at least one call to health personnel (mainly to the nurse or specialist), 1 change of therapy, and low-level home emergency assistance, only 43% of patients being free from exacerbations and recourse to hospitalization. The most frequent users of HTP were the worst patients, i.e., those presenting exacerbations, who had an increased need for ABGs to diagnose chronic respiratory failure and a higher frequency of unscheduled GP review. These results correlate with previous findings from the Eclipse study (Citation24) in which the history of hospitalizations or COPD exacerbations in the year before the intervention was the best predictor of new episodes, respectively. By contrast, gender, age, BMI, presence of co-morbidities, GOLD stage, geographical location, oxygen use and clinical history before HTP start seem not to influence the use of telemanagement services. These results confirm that an HTP may be useful at any age (Citation10), in different geographical settings, and in patients with less severe functional level.
One-third of the whole sample presented a relapse without need for hospitalization during the course of the program. Multivariable regression analysis showed that smokers/ex-smokers, specialist and GP consultation users had a strong risk for relapse with an accuracy prediction of 72.9%. The higher risk for relapse in smokers has been previously demonstrated (Citation25), while the close relation between relapses and physician need (both specialist and GP) seems self-apparent. This finding confirms the burden caused by COPD, with a vicious circle represented by functional severity, clinical history, health costs and time consuming demands on health operators (Citation1, Citation26).
One-third of all patients were hospitalized (the majority were not related to COPD) during the course of the program. Our study failed to demonstrate a clear and strong index or condition related to hospitalization risk; in fact, recourse to hospitalization is often motivated by multiple, unknown and unreported conditions and decisions related to physicians’ local habits.
Any integrated care program, as with an HTP, has the aim to lessen or at least to contain as far as possible the impact of COPD disease. It is not surprising that a high impact of disease measured by the CAT score at the end of our HTP program was directely related to patients’ severity as demonstrated by the amount of co-morbidities and to the CAT score at baseline, while it was inversely related to LTOT prescription/use or to a stable condition at admission.
A real-life retrospective review such as this one performed in the Lombardy Region may be useful to health authorities in managing national HTPs as it can highlight subgroups of patients in whom tele-health is most used (and thus presumably of most benefit) and those for whom it is of little advantage, so that they can adjust the inclusion criteria accordingly, and it can help them predict early failure of tele-health (Citation4). In addition, our results could be useful for allocating different levels (more or less technology and/or type of personnel) and prescribed length (hours/day, months of follow-up) of an HTP service to different categories of patients: i.e., a more aggressive service for exacerbators, ABG and GP consultation users, while a less aggressive service for the others.
Based on the literature (Citation3–5,Citation7–16), the number of patients with COPD involved in previous HTPs ranged from 4 to 369 with the percentage of drop-outs ranging from 1.3% to 26%. In our study, the pathway was interrupted early in 232 patients (22%) due to death, new prevailing disease, or hospitalization, confirming that the reasons to interrupt the service were related to patients’ functional and disability severity rather than to hospital team organizational problems.
The relatively low rate of enrollment per centre (apart from the Varese Units including two different hospitals) may be explained by the current Italian hospital administrative organization in terms of infrastructure, accreditation, certification, labelling, budget, and undefined legal and regulatory questions concerning this new healthcare approach as a potential administrative problem without a robust reimbursement scheme. This could have influenced the generalizability of the study findings.
Limitations of the study are its observational nature and the arbitrary criteria used to define the subgroups (i.e., cut-off values of the parameters). We are confident, nevertheless, that the study patients are representative of chronic patients usually admitted to respiratory departments. In a real-life study, a control group is not always possible especially where clinical effectiveness is not the aim, as in our case.
A major strength of this study is the large size of the real-life patient cohort which offers important health organizational messages: the study could provide a useful benchmarking picture for those interested in implementing HTPs in COPD in terms of aiding them in their decisions as regards personnel investment, reduction of redundancy and duplication of care services, and prioritization of services. Other strengths are the uniform and standardized intervention protocol adopted, the quality of the clinical and technological intervention, the round-the-clock availability of the HTP call service, and the interdisciplinary nature of the care pathway proposed (involving nurses, specialist and GP), which likely contributed to an overall improvement of patients’ lifestyle and self-management capacities.
In conclusion, the experience of HTP for patients with COPD in Lombardy shows that exacerbators, people needing several ABGs and urgent GP visits are the patient subgroup most likely to require more health care utilization and, in this case, make more use of telemanagement services. We propose a patient “identikit” to improve prioritization for HTP prescription.
Acknowledgments
The authors would like to thank the Lombardy Region. Healthcare Directorate (BERGAMASCHI Walter, TRIDICO Caterina, BERSANI Maurizio). and the health professionals of all hospitals involved in “Nuove Reti Sanitarie”( AO di Bergamo (Piero Arnone); AO di Seriate - P.O. Piario (LAZZARONI Sergio); AO Desenzano del Garda (ELESBANI Olivia); AO di Chiari (SERENI Daniela) ; Casa di Cura Domus Salutis - Brescia (ALIPRANDI Giovanni); Fondaz. Don Carlo Gnocchi - Centro Riabilitazione E. Spalenza – Rovato (TESTA Amidio); Centro Ortopedico Fisiatrico Lanzo Hospital (BOCCHIA Mario Ernesto); AO di Crema (AIOLFI Stefano); INRCA Casatenovo (GUFFANTI Enrico Eugenio); AO della Provincia di Lodi (TURSI Francesco); AO di Mantova (STURANI Carlo/COMEL Andrea); AO Luigi Sacco - Milano (RIZZI Maurizio); AO San Carlo Borromeo - Milano (AMADUCCI Sandro/ PIETRA Attilio) Fondaz. Salvatore Maugeri - Via Camaldoli - Milano (SANTUS Pierachille); ICP Milano - P.O. Città di Sesto San Giovanni (FORESI Antonio); ICP Milano - P.O. CTO - Milano (RIARIO SFORZA Gian Galeazzo); AO della Provincia Pavia (MAZZOCCHI Paolo); Fondaz. Salvatore Maugeri - Montescano (FRACCHIA Claudio); Fondaz. Salvatore Maugeri - Pavia (NAVA Stefano/ CERIANA Piero); AO Valtellina Valchiavenna (PAPALIA Antonella); ASL Vallecamonica Sebino (TONDINI Maurizio/SALADA Luisa); AO di Busto Arsizio (ZANON Pietro). The authors are also indebted to Dr Laura Comini, Ottavia Turla and Rosemary Allpress for technical assistance and language revision.
Declaration of interest statement
The authors report no conflicts of interest. The authors take responsibility for all aspects of the reliability and freedom from bias of the data presented and their discussed interpretation. The authors alone are responsible for the content and writing of the paper.
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