Are degree of urbanisation and travel times to healthcare services associated with the processes of care and outcomes of heart failure? A retrospective cohort study based on administrative data.

A few studies have found that patients with heart failure (HF) living in less densely populated areas have reduced use of services and poorer outcomes. However, there is a lack of evidence regarding transport accessibility measured as the actual distance between the patient's home and the healthcare facility. The aim of this study was to investigate if different urbanisation levels and travel times to healthcare services are associated with the processes of care and the outcomes of HF. This retrospective cohort study included patients residing in the Local Healthcare Authority of Bologna (2915 square kilometres) who were discharged from hospital with a diagnosis of HF between 1 January and 31 December 2017. Six-month study outcomes included both process (cardiology follow-up visits) and outcome measures (all-cause readmissions, emergency room visits, all-cause mortality). Of the 2022 study patients, 963 (47.6%) lived in urban areas, 639 (31.6%) in intermediate density areas, and 420 (20.8%) in rural communities. Most patients lived ≤30 minutes away from the nearest healthcare facility, either inpatient or outpatient. After controlling for a number of individual factors, no significant association between travel times and outcomes was present. However, rural patients as opposed to urban patients were more likely to see a cardiologist during follow-up (OR 1.42, 99% CI 1.03-1.96). These follow-up visits were associated with reduced mortality within 6 months of discharge (OR 0.53, 99% CI 0.32-0.87). We also found that multidisciplinary interventions for HF were more common in rural than in urban settings (18.8% vs. 4.0%). In conclusion, travel times had no impact on the quality of care for patients with HF. Differences between urban and rural patients were possibly mediated by more proximal factors, some of which are potential targets for intervention such as the availability and utilisation of follow-up cardiology services and multidisciplinary models of care.

Introduction

Heart failure (HF) is a complex clinical syndrome with a prevalence of 1 to 2% in the adult population of Western countries, a value that exceeds 10% in individuals over 70 years of age [1,2]. The prognosis is poor, with an in-hospital mortality of 10% and a one-year mortality after discharge of 20 to 40% [3-8]. HF is one of the main reasons for hospital admission in Europe and the US [9], especially for patients over 65 years [10], and the readmission rate exceeds 20% and 50% within a month and a year of hospital discharge, respectively [11,12]. Patients require a care approach that takes into account all their complex care needs [13], and indeed it has been shown that easy access to care is a significant determinant of their outcomes [14].

A recent systematic review regarding accessibility in terms of distance and travel time from the patient’s home, showed that individuals living near healthcare facilities have better health outcomes or a higher rate of access to services than those living further away [15]. However, this review included mainly cancer research studies relying on different data sources and variables.

With respect to HF, a few studies found that living in less densely populated areas was associated with reduced use of services and poorer outcomes [16-18]. These findings should be read keeping in mind that geographic position might have a close correlation with a large number of variables, such as socioeconomic status (SES), availability of appropriate services, and even peculiar clinical conditions. A potential limitation of these studies is the lack of information regarding transport accessibility measured as the actual distance between the patient’s home and the healthcare facility.

The Local Healthcare Authority (LHA) of Bologna, located in the Emilia-Romagna region of Italy, has various hospitals and primary care services in its territory. Over the past few years, an increasing number of healthcare homes and ambulatory care nursing practices have been established, where patients are medically examined and receive outpatient nursing interventions for lifestyle change or for the control and management of their own health problems. Many of the interventions included in the care pathways (CPs), such as the heart failure CP (HF-CP), are also provided within these care settings. This multidisciplinary and standardised CP promotes the integration of different services and professionals, and aims to improve the health status of the patients with HF through a direct and easy access to care.

Despite the large number of healthcare facilities and the efforts to improve patients’ access to services, the catchment area of Bologna has a relatively diverse geography and uneven population distribution. Therefore, the objective of this study was to investigate whether different travel times to healthcare services in the LHA of Bologna are associated with the processes of care and the outcomes of patients with HF. In keeping with existing literature, we also evaluated the impact of urbanisation levels on the study processes and outcomes.

Materials and methods

Setting and study population

This retrospective observational study included all hospital discharges in the LHA of Bologna with a primary diagnosis of HF (ICD-9-CM codes: 398.91, 402.x1, 404.x1, 404.x3, 428.xx) between 1 January and 31 December 2017. The LHA of Bologna is located in the northeast of Italy, has a population of about 876,000 and covers an area of 2915 km2, with a territory that is 29% mountains (the Apennines), 32% hills, and 39% plains (the Po Valley) (Figure A in S1 Fig).

Data were retrieved from the Hospital Discharge Records (HDRs) Database (this and the other data sources used in this study are described in S1 Table) [19]. For patients with multiple eligible hospital admissions over the one-year study period, we considered the first one as the index admission. Repeated admissions within one day of discharge were regarded as one single episode of care, and the beginning of the follow-up was set at the discharge date of the episode of care. All patients were followed up to 6 months.

Patients were excluded if any of the following criteria were met (S2 Fig):

Permanent and/or current address outside the LHA catchment area

Homeless

Registered at a general practitioner (GP) who practiced outside the catchment area

Age >100 years, because very old patients may have distinctive clinical features at diagnosis and survival

Planned hospital admission, to focus analyses on acute/urgent episodes of care

Transfer from another facility, to focus analyses on incident cases of HF

Daytime hospital care, i.e., one-day admissions to the hospital without overnight stay to perform diagnostic procedures and/or surgical, therapeutic or rehabilitative care

A secondary diagnosis of non-cardiogenic acute pulmonary oedema (ICD-9-CM 518.4), i.e., patients with symptoms probably related to causes other than HF

A secondary diagnosis of acute kidney failure (ICD-9-CM 584.x), i.e., patients whose reason for hospitalisation is likely not to be HF

Pregnancy, childbirth or puerperium (Major Diagnostic Category 14)

A major procedure on the cardiovascular system (ICD-9-CM 00.5x, 00.66, 35.xx, 36.xx, 37.31–37.66, 37.70–37.89, 37.94–37.98), i.e., patients with severe cardiac impairment as the main reason for hospitalization

Death during the index episode of care

Discharge against medical advice

Length of stay >90 days, i.e., very complex or unstable cases

Access to residential care facility for the elderly before index hospitalisation or during follow-up, i.e., patients being given end-of-life care.

Study outcomes

The 6-month outcomes evaluated in this study included both process and outcome measures:

Cardiology follow-up visits provided in either outpatient or inpatient cardiology services, except for those booked prior the index admission or performed during hospital stays (source: Outpatient Care Database [OCD])

All-cause unplanned readmissions occurred at any hospital within 2 to 180 days of discharge, and lasting >1 day (source: HDRs)

Emergency room (ER) visits not related to injuries and not resulting in inpatient admission (source: ER database)

All-cause mortality (source: vital registration system).

Degree of urbanisation

Using the Eurostat’s Degree of Urbanisation (DEGURBA) classification system (revised definition, 2014), the 45 municipalities (comuni) where the patients lived were subdivided into rural areas (alternative name: sparsely populated areas), towns or suburbs (intermediate density areas), and cities (densely populated areas). As illustrated in Figure B in S1 Fig, the city of Bologna was classified as urban (388,000 pop., 44%), the nearby comuni and other areas in the Po Valley were classified as towns or suburbs (304,000 pop., 35%), while the remaining comuni—both flat and mountainous—were classified as rural (184,000 pop., 21%).

Travel times to healthcare services

Because of the catchment area’s diverse geography, we calculated the travel times between the patients’ home addresses (source: civil registry) and a series of healthcare facilities that provide care for patients with HF. These included:

Emergency rooms (N = 12)

Cardiology wards (N = 5)

Outpatient cardiology services (N = 27)

Ambulatory care nursing practices (N = 34), 15 of which are located in the healthcare homes

GP practices (N = 739), run by a total of 525 GPs.

Due to proximity to the border, three hospitals providing emergency and/or cardiology care outside the LHA catchment area were included in the study.

After geocoding all locations in the WGS84 spatial reference by means of the Stata opencagegeo package, the travel times between geographic coordinates were computed using the georoute package [20,21]. georoute calculates how long it takes to drive the distance between two points under average traffic conditions [21].

To account for potential nonlinear relationships with the outcomes, travel times were split into five categories: ≤5 min (very short), >5–10 min (short), >10–20 min (medium), >20–30 min (long), and >30 min (very long).

In addition to the degree of urbanisation, different sets of routing distances were considered as the potential predictors of each study outcome. When we analysed cardiology follow-up visits, the travel time of interest was to the nearest cardiology service, either inpatient or outpatient. In all the other analyses, we considered three distinct travel times: to the nearest ER, the nearest patient’s GP practice, and the nearest outpatient service, either cardiologist or non-cardiologist. Moreover, follow-up cardiology visits were treated as potential predictors of hospital readmissions, ER visits and mortality [22-24]. An overview of these sets of variables is provided in S2 Table.

Potential confounders

We collected some patient baseline characteristics to reduce the potential source of confounding. These included:

Age

Sex

Citizenship

Length of stay

Provision of intensive care during hospital stay

Discharge from a cardiology ward

Thirty-one Elixhauser conditions identified in the index episode of care and in all hospital admissions occurring two-years prior to the index hospitalisation [25], plus four additional conditions not included in the Elixhauser’s list (myocardial infarction [ICD-9-CM 410.x, 412], cerebrovascular diseases [362.34, 430.x–438.x], dementia [290.x, 294.1, 331.2], leukaemia [204.x-208.x])

Use of 10 drug therapies one-year prior to the index admission (≥1 filled prescription) (source: Outpatient Pharmaceutical Database).

See Tables A and B in S3 Table for the detailed list of drug therapies and Elixhauser comorbidities. We also took into account the following information in the analyses [19,26-29]:

Use of first-line medications during follow-up, that is, angiotensin-converting enzyme inhibitors/angiotensin receptor blockers (ACEIs/ARBs) and β-blockers (only for hospital readmission, ER visit and mortality analyses)

Registration at occasional or full-time general home-care services as a proxy of social and medical complexity

Registration at the HF-CP, a structured multidisciplinary care plan that promotes integration between primary and secondary care, and details essential steps in the care of patients. The GP remains the gatekeeper for the patients and coordinates with cardiologists and nurses for an easier access to consultation and counselling to improve lifestyle and optimise medication adherence. The HF-CP can involve either outpatient clinic-based interventions (clinic-based HF-CP) or home visits (home-based HF-CP), depending on the patient’s clinical condition and ability to move. There are no facilities specifically dedicated to the HF-CP: registered patients can access GP practices, cardiology services or ambulatory care nursing practices in case they need medical care or counselling.

The patient could already be registered at the beginning of the follow-up, or access the outpatient services following discharge. Information on outpatient care was collected from regional and LHA administrative databases. All the data sources used in this study are de-identified and linkable using the unique patient identifier.

As previously mentioned, cardiology visits during follow-up were included in regression analyses as potential predictors of hospital readmission, ER visits and mortality [19,22-24].

Statistical analysis

Continuous variables were summarised as mean ± standard deviation; discrete and categorical variables were summarised as frequencies and percentages. Comparisons across urbanisation levels were performed using one-way analysis of variance, Kruskal-Wallis test or chi-squared test, when appropriate. The spatial distribution of homes and healthcare facilities was graphically displayed with the aid of dot maps.

To ensure an equal time window for detecting and measuring time-varying covariates, such as outpatient care and medication use (see section above), the impact of urbanisation level and travel times on the study outcomes was assessed using a time-matched nested case-control design. Patients who experienced the study outcome were defined as cases, and 9 controls were randomly selected and matched to each case by gender, age group (defined using a decile split) and follow-up duration. This technique is called “incidence density sampling”. Odds ratios (ORs) were estimated by conditional logistic regression models to account for the matching of cases and controls [19].

All regression models included the potential confounders described earlier. However, to avoid overfitting and misclassification, not all comorbidities and previous drug therapies were included in the models. A subset of all candidate variables was preliminary chosen for inclusion using an automated selection method which is described in detail elsewhere [19,30]. In brief, a bootstrap procedure was adopted to determine which comorbidities were significantly associated with the outcomes. Using this approach, a backward elimination of potential confounders was applied in each replicated sample with a significance level or removal equal to 0.05, and only risk factors selected in at least 50% of the replicates were included as confounders in the final multivariable regression models. The confounders included in the final models are reported in table footnotes. The variance inflation factor, a measure of correlation among predictor variables (multicollinearity), was <3 for all of the predictors included in the models.

To control for type I error related to multiple testing, the significance level was set at 0.01. All analyses were carried out using Stata software, version 15 (StataCorp. 2017. Stata Statistical Software: Release 15. College Station, TX: StataCorp LLC).

Ethics statement

Ethical approval to undertake this research was granted from the Comitato Etico di Area Vasta Emilia Centro (Submission Number 254/2019/OSS/AUSLBO).

This retrospective study was carried out in conformity with the regulations on data management with the Italian law on privacy (Legislation Decree 196/2003 amended by Legislation Decree 101/2018). Data were pseudonymised prior to the analysis at the regional statistical office, and each patient was assigned a unique identifier that eliminates the ability to trace the patient’s identity or other sensitive data. Pseudonymised administrative data can be used without a specific written informed consent when patient information is collected for healthcare management and healthcare quality evaluation and improvement (according to art. 110 on medical and biomedical and epidemiological research, Legislation Decree 101/2018).

Patients and the public were not involved in the design or planning of the study. All procedures performed in this study were in accordance with the 1964 Helsinki Declaration and its later amendments.

Results

Of the 3138 patients discharged after HF, 2022 (64.4%) met the inclusion criteria (S2 Fig). Mean age was 82.2 ± 9.5 years and 1089 (53.9%) were females. A total of 963 (47.6%) patients lived in densely populated areas, 639 (31.6%) lived in intermediate density areas and 420 (20.8%) lived in rural areas. As shown in Table 1, patients living in rural areas were on average younger, more often registered at the HF-CP and more often discharged from internal medicine services. Specific comorbidities and previous drug therapies are summarised in Tables A and B in S4 Table.

Table 1

Distribution of patient characteristics and travel times, overall and by degree of urbanisation.

Patient characteristics	All		City		Towns and suburbs		Rural areas		P
	(n = 2022)		(n = 963)		(n = 639)		(n = 420)
	n	%	n	%	n	%	n	%
Females	1089	53.9	537	55.8	340	53.2	212	50.5	0.178
Age, mean ± SD	82.2 ± 9.5		82.8 ± 9.6		82.1 ± 8.9		80.9 ± 10.0		0.002
Non-Italians	35	1.7	21	2.2	9	1.4	5	1.2	0.324
Length of stay, mean ± SD	8.0 ± 4.8		9.3 ± 7.4		8.9 ± 7.6		9.3 ± 7.1		0.686
Two or more comorbidities	1705	84.3	795	82.6	539	84.4	371	88.3	0.060
Two or more previous drug therapies	1729	85.5	807	83.8	554	86.7	368	87.6	0.212
Discipline of the ward of discharge									<0.001
Internal medicine	1436	71.0	645	67.0	449	70.3	342	81.4
Geriatrics	285	14.1	165	17.1	84	13.1	36	8.6
Cardiology	272	13.5	136	14.1	97	15.2	39	9.3
Other	29	1.4	17	1.8	9	1.4	3	0.7
Intensive care	67	3.3	27	2.8	22	3.4	18	4.3	0.358
Use of ACEIs/ARBs	1042	51.5	499	51.8	334	52.3	209	49.8	0.706
Use of β-blockers	1457	72.1	671	69.7	461	72.1	325	77.4	0.013
Use of both ACEIs/ARBs and β-blockers	817	40.4	384	39.9	263	41.2	170	40.5	0.877
HF care pathway									<0.001
No	1817	89.9	924	96.0	552	86.4	341	81.2
Clinic-based	115	5.7	31	3.2	35	5.5	49	11.7
Home-based	90	4.5	8	0.8	52	8.1	30	7.1
General home care									0.635
No	497	51.6	310	48.5	221	52.6	1028	50.8
Occasional	50	5.2	38	5.9	20	4.8	108	5.3
Full-time	416	43.2	291	45.5	179	42.6	886	43.8
Travel time to nearest ER									<0.001
Very short (≤5 min)	199	9.84	118	12.30	23	3.60	58	13.81
Short (>5–10 min)	755	37.34	622	64.59	72	11.27	61	14.52
Medium (>10–20 min)	837	41.39	221	22.90	441	69.01	175	41.67
Long (>20–30 min)	191	9.40	2	0.21	101	15.81	88	21.00
Very long (>30 min)	40	1.98	0	0.00	2	0.31	38	9.00
Travel time to nearest patient’s GP practice									0.001
Very short (≤5 min)	1,328	65.7	634	65.8	440	68.9	254	60.5
Short (>5–10 min)	424	21.0	227	23.6	120	18.8	77	18.3
Medium (>10–20 min)	215	10.6	97	10.1	59	9.2	59	14.0
Long (>20–30 min)	35	1.7	2	0.2	17	2.7	16	3.8
Very long (>30 min)	20	1.0	3	0.3	3	0.5	14	3.3
Travel time to nearest cardiology service, either inpatient or outpatienta									<0.001
Very short (≤5 min)	865	42.8	478	49.6	291	45.5	96	22.9
Short (>5–10 min)	775	38.3	468	48.6	195	30.5	112	26.7
Medium (>10–20 min)	270	13.4	17	1.8	122	19.1	131	31.2
Long (>20–30 min)	87	4.3	0	0.0	31	4.9	56	13.3
Very long (>30 min)	25	1.2	0	0.0	0	0.0	25	6.0
Travel time to nearest ambulatory care nursing practice									<0.001
Very short (≤5 min)	1040	51.4	553	57.4	371	58.1	116	27.6
Short (>5–10 min)	734	36.3	401	41.6	207	32.4	126	30.0
Medium (>10–20 min)	209	10.3	9	0.9	61	9.5	139	33.1
Long (>20–30 min)	39	1.9	0	0.0	0	0.0	39	9.3
Very long (>30 min)	0	0.0	0	0.0	0	0.0	0	0.0

SD, standard deviation; ACEIs/ARBs, angiotensin-converting enzyme inhibitors/angiotensin receptor blockers; HF, heart failure; ER, emergency room; GP, general practitioner.

a Nearest cardiology ward or outpatient cardiology service.

Travel times are summarised in Table 1, while the spatial distribution of HF patients and healthcare services in the LHA catchment area is illustrated in Fig 1. Although outpatient healthcare services were relatively scattered as compared to inpatient services, most patients lived ≤30 minutes away from the nearest facility. Still, we found that travel times were significantly dependent on urbanisation, as patients living in rural communities were more distant from all healthcare services than those living in more densely populated areas.

Fig 1

Dot map of patient’s homes and inpatient/outpatient healthcare services, Local Healthcare Authority of Bologna, year 2017.

The shapefiles used to make this figure are made publicly available by the Italian National Institute of Statistics. Administrative boundaries reproduced from [31] under a CC BY license, with permission from the Italian National Institute of Statistics, original copyright 2019.

The outcomes rates over the 6-month observation period, overall and by degree of urbanisation, are reported in Table 2. There was a lower rate of cardiology visits among patients living in Bologna. No other crude associations between urbanisation level and outcomes were found.

Table 2

Outcomes rates (%) at 6 months after heart failure discharge, overall and by degree of urbanisation.

Six-month study outcome	All		City		Towns and suburbs		Rural areas		P
	(n = 2022)		(n = 963)		(n = 639)		(n = 420)
	n	%	n	%	n	%	n	%
Cardiology follow-up visita	649	32.1	272	28.2	224	35.1	153	36.4	0.002
All-cause unplanned readmission	726	35.9	357	37.1	213	33.3	156	37.1	0.261
ER visit not resulting in inpatient admissionb	487	24.1	213	22.1	168	26.3	106	25.2	0.132
All-cause mortality	391	19.3	190	19.7	119	18.6	82	19.5	0.855

a Of the 649 patients with cardiology follow-up visits, 91 (14.0%) were seen within 14 days of discharge, 195 (30.0%) within 28 days and 484 (74.6%) within 90 days.

b Of the 487 patients seeking emergency care, 362 (74.3%) accessed the nearest ER.

The impact of urbanisation levels and travel times resulting from multivariable regression analysis is presented in Tables 3 and 4. After adjusting for travel times and other patient characteristics (see table footnotes), we found that rural patients were more likely to see a cardiologist (OR 1.42, 99% CI 1.03–1.96), compared with urban patients. No other significant association between predictors and outcomes was present.

Table 3

Impact of urbanisation level and travel time to the nearest cardiology service on the likelihood of seeing a cardiologist within 6 months of heart failure discharge.

Urbanisation and travel times	Cardiology follow-up visit
	ORa	99% CI
Degree of urbanisation
City	1.00
Towns or suburbs	1.17	0.90–1.52
Rural area	1.42b	1.03–1.96
Travel time to nearest in- or outpatient cardiology service
Very short (≤5 min)	1.00
Short (>5–10 min)	0.86	0.67–1.10
Medium (>10–20 min)	0.95	0.68–1.34
Long (>20–30 min)	0.63	0.35–1.14
Very long (>30 min)	0.54	0.17–1.67

OR, odds ratio; CI, confidence interval.

a Adjusted for age, sex, length of stay, intensive care, discharge from cardiology, dementia, and general home care/HF care pathway during follow-up.

b Significant at the 0.01 level.

Table 4

Impact of urbanisation level and travel times to healthcare services on hospital readmissions, emergency room visits and mortality within 6 months of heart failure discharge.

Urbanisation and Travel Times	All-Cause Unplanned Readmission		ER Visit		All-Cause Mortality
	ORa	99% CI	ORb	99% CI	ORc	99% CI
Degree of urbanisation
City	1.00		1.00		1.00
Towns or suburbs	0.77	0.57–1.04	1.10	0.37–2.03	0.96	0.63–1.48
Rural area	0.85	0.60–1.19	1.26	0.95–1.67	0.96	0.57–1.53
Travel time to nearest ER
Very short (≤5 min)	1.00		1.00		1.00
Short (>5–10 min)	0.96	0.66–1.39	0.76	0.48–1.20	0.83	0.50–1.39
Medium (>10–20 min)	1.13	0.77–1.67	0.87	0.55–1.3	1.13	0.66–1.93
Long (>20–30 min)	1.36	0.79–2.32	0.92	0.49–1.74	2.08	0.99–4.35
Very long (>30 min)	1.03	0.45–2.37	0.22	0.04–1.11	0.66	0.15–2.94
Travel time to nearest practice of the patient’s GP
Very short (≤5 min)	1.00		1.00		1.00
Short (>5–10 min)	1.04	0.79–1.36	1.10	0.80–1.52	1.18	0.81–1.71
Medium (>10–20 min)	1.17	0.83–1.65	0.92	0.60–1.42	1.14	0.70–1.83
Long (>20–30 min)	1.59	0.70–3.61	0.65	0.21–1.99	0.72	0.20–2.58
Very long (>30 min)	1.22	0.42–3.54	0.37	0.06–2.46	3.42	0.87–13.46
Travel time to nearest outpatient service, either card. or non-card.
Very short (≤5 min)	1.00		1.00		1.00
Short (>5–10 min)	0.87	0.69–1.10	0.98	0.74–1.30	1.12	0.81–1.57
Medium (>10–20 min)	0.83	0.54–1.28	0.96	0.59–1.55	0.60	0.31–1.14
Long (>20–30 min)	1.10	0.49–2.49	0.87	0.25–3.01	1.61	0.51–5.03

a Adjusted for age, sex, length of stay, intensive care, discharge from cardiology, history of heart failure, diabetes, chronic kidney disease, previous use of ACEIs/ARBs, and general home care/HF care pathway/cardiology visit/use of first-line medications during follow-up.

b Adjusted for age, sex, length of stay, intensive care, discharge from cardiology, and general home care/HF care pathway/cardiology visit/use of first-line medications during follow-up.

c Adjusted for age, sex, length of stay, intensive care, discharge from cardiology, history of heart failure, cardiac arrhythmias, chronic kidney disease, dementia, previous use of diuretics/statins, and general home care/HF care pathway/cardiology visit/use of first-line medications during follow-up.

Other outcome predictors

The full multivariable regression models including travel times and processes of care, both inpatient and outpatient, are presented in Tables A and B in S5 Table. The main results can be summarised as follows:

Patients registered at the clinic-based HF-CP were more likely to be seen by a cardiologist during follow-up (OR 1.69, 99% CI 1.02–2.80)

As compared with patients with no cardiology follow-up visits, patients seen by a cardiologist during follow-up were less likely to die within 6 months of discharge (OR 0.53, 99% CI 0.32–0.87).

Discussion

The main result of this retrospective cohort study was that urbanisation and travel times to healthcare services had no impact on the processes of care and the outcomes of patients with HF in the 6 months following hospital discharge. The only exception was that cardiology follow-up visits were more frequent among rural than among urban patients. We also found that patients registered at the clinic-based HF-CP were more likely to see a cardiologist during follow-up, and that outpatient cardiology care was associated with improved outcomes.

These results were obtained after controlling for several potential individual confounders. However, our administrative databases do not include very relevant clinical information, such as left ventricular ejection fraction and classification of disease severity, which can affect the patient outcomes.

To the best of our knowledge, this is the first study to evaluate whether the care of patients with HF is associated with transport accessibility to healthcare, measured as the travel time to a number of different services and facilities. A strength of our method is that the patient’s home address was the starting point to measure the travel times, while a potential limitation is that these calculations were made assuming that all patients would attend the nearest facility. Another strength is that our estimates of driving times were not only a function of driving distances [15,32], but also depended on average traffic volumes, road conditions and elevation. Nevertheless, travel time is only a component of the travel burden for these patients, who are elderly and can face a relevant combination of barriers due to disabilities, clinical conditions and comorbidities, and need for multiple medical assessments [33]. Also, often elderly patients must be accompanied by their caregivers, whose availability depends, among other things, on the opportunity to take some time off work or to delegate the care of children. This important aspect would deserve further investigation, but administrative databases do not provide any information on informal caregivers.

In addition to travel times, we analysed the degree of urbanisation of the community where the patient lived, a measure adopted in many other studies [15,16,18,34]. As expected, we found that travel times were longer for patients living in less densely populated areas. However, contrary to other studies that found poorer outcomes among rural residents [15,16,18,35,36], we found that rural patients had more follow-up cardiology visits. The better access to follow-up care by rural patients might be explained by a seamless organisation of care that is easier to implement in non-urban communities than in metropolitan settings, where the higher number of providers and facilities can make paradoxically more complex to refer patients to the same professionals. To support this, we found that rural patients were more commonly registered at the HF-CP, whose aim is to standardise care and to define the reference professional for the patient.

Still, no other significant associations between degree of urbanisation and outcomes were present in this study. Although urbanisation level is commonly seen as a proxy for SES and other SES-related characteristics [17], one possible explanation is that such inequalities are not unevenly distributed across the LHA of Bologna. Another possible explanation is that the strong universal health coverage of Italy might play a role in reducing inequalities in access to healthcare, as suggested by a study evaluating the relationships between SES and HF outcomes in a universal national health service [37]. However, we lack updated information on census track-level SES in our catchment area, and the available data are not equipped to disentangle the association between geography and SES among patients with HF.

Because geographic location is also a proxy for the availability of appropriate healthcare facilities, some studies hypothesised that the worst outcomes of rural patients are due to lack of appropriate healthcare and to limited access to specialist services [16,17,35,38]. However, a strength of our study is that we adjusted all analyses for provision of HF-CP and inpatient/outpatient cardiologist care, which are known (and we found) to correlate with better outcomes [14,19,24,29,38,39]. Involvement of cardiologists in the management of patients with HF might reduce mortality and readmissions and enhance adherence to guideline treatments by endorsing or refining GP recommendations. Moreover, the collaboration with GPs and outpatient nurses can provide additional monitoring of the patients’ concerns and adherence as planned in the CP [19,29,38]. Still, a shortcoming of our analysis is that the number of GP visits for each patient, either registered or not registered at the HF-CP, is not available. In Italy, most GPs use dedicated computer programmes to manage rosters, appointments and clinical data, but this information cannot be accessed by the local healthcare authorities.

Although rural patients had more follow-up cardiology visits (X → M) and these visits were associated with lower mortality (M → Y), we did not find evidence of reduced mortality among rural patients (X → Y). This should come as no surprise because, as a causal process becomes more distal, the size of the effect typically gets smaller and ultimately fails to achieve statistical significance [40]. A possible interpretation is that the relationship between geographic location and mortality acts via a number of many other intermediary links, competing risks and random factors.

Study limitations

As mentioned above, there are a number of limitations to our study. First, we lack some relevant information, including clinical features, disease severity, SES, informal caregivers, and GP visits. Second, we assumed that all patients would attend the nearest facility. Third, travel times do not fully depict the travel burden of patients with HF, who are elderly and can be hindered by a relevant combination of disabilities and clinical conditions.

Conclusions

Our findings show that the travel times to healthcare services have no impact on the quality of care for patients with HF. Possible reasons for this result include the large number of healthcare services in the LHA of Bologna and the relatively short driving distances to the nearest facility (mostly <30 minutes), which can harm the generalisability of this study to rural areas with remote and isolated communities. We also found that the impact of the degree of urbanisation was possibly mediated by more proximal factors, some of which are potential targets for intervention such as the availability and utilisation of different types of care settings. More specifically, we found that cardiology services and multidisciplinary models of care had an impact on the quality of care for patients with HF.

When geographic accessibility is generally good, healthcare delivery and patient outcomes can be optimised by prioritising high-quality models of care, not only the quantity of available services being provided. This is particularly relevant considering the ageing of populations, the increase in disabilities and chronic diseases, and the downward trend of available healthcare resources for patients with complex needs.

Because the effectiveness of such composite programmes is context-specific, further research is needed to guide, tailor and improve healthcare settings and interventions to manage the clinical complexity and frailty of patients with HF.

Supporting data.

(XLS)

Click here for additional data file.

Maps of the Local Healthcare Authority of Bologna, Northern Italy.

(PDF)

Click here for additional data file.

Diagram depicting selection of the study population.

GP, general practitioner.

(PDF)

Click here for additional data file.

Description of data sources.

(PDF)

Click here for additional data file.

Six-month study outcomes, degree of urbanisation and travel times to healthcare.

ER, emergency room; GP, general practitioner; FUP, follow-up.

(PDF)

Click here for additional data file.

Comorbidities and drug therapies considered for inclusion in multivariable regression models.

(PDF)

Click here for additional data file.

Distribution of comorbidities and previous medication use in the study population.

(PDF)

Click here for additional data file.

Association of processes of care, urbanisation levels and travel times with the study outcomes of patients with heart failure.

(PDF)

Click here for additional data file.

21 Aug 2019

PONE-D-19-20409

Are degree of urbanisation and travel times to healthcare services associated with the processes of care and outcomes of heart failure? A retrospective cohort study based on administrative data

PLOS ONE

Dear Dr. Avaldi,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

==============================

ACADEMIC EDITOR:

In addition to the points raised by the reviewers, I would like you to address the following points:

1) It is acceptable that not all information on the methods is provided in the text if previously published. Still, the readers must be able to understand the methods without reading the cited paper. This means that that a short description of the according parts of the methods is required. Only citing a previous study is not sufficient.

2) The authors include some limitations of their analysis but lack to mention all of them. The reviewers addressed some of them and they also made suggestions that can possibly not be addressed based on the administrative data set. The authors must clearly address this. In this regard, a very important shortcoming is that there is no information on the severity of HF.

3) Instead of repeating findings previously mentioned as part of the discussion / conclusion, the authors should focus more on the reasons why they think that their findings are in some contrast to other findings and possibly also their expectations (a clear hypothesis would help in this regard), more thoughts about the potential clinical implications and future perspectives, considering expected changes in healthcare in the future (as in part also addressed by the reviewers). If the authors do not want to extend too much regarding length of the text, the introduction can be shortened. This particularly refers to the extensive discussion about the burden of heart failure. This is well known, mentioned in thousands of papers, and can therefore be shortened significantly.

4) Please check that the references to tables and figures are correct. Suppl. text 1 is a figure. Please check that the manuscript follows the requirements of the journal regarding format, placement of tables, figures, references etc.

==============================

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Hans-Peter Brunner-La Rocca, M.D.

Academic Editor

PLOS ONE

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1. Given the retrospective design, the study can only draw conclusions about an association, please revise the language in the manuscript (and abstract) which refers to an ‘impact’ (or lack of ‘Impact’) of urbanisation and travel times to healthcare services on outcomes of heart failure or similar causal language, to refer to an association.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Dear Author,

Many thanks for the opportunity to review this interesting manuscript examining the relationship between urbanisation and travel time with processes of care and heart failure outcomes. In general it was well written and structured with transparency and rigour from data to conclusion. I would like to make few comments which I would like your consideration.

In terms of participant characteristics, it would have been beneficial to know NYHA class &/or the EF. This was particularly pertinent as on review of Table 1, 18 (4.3%) of rural compared to 27 (2.8) city and 22 (3.4) towns & suburbs were discharged from intensive care. Was there a difference in the "sickness" of the patients"?

Figure 1 demonstrated a numerous GP practices and centralised cardiology wards. Can I ask why GP visits were not recorded or included as a study outcome?

Use of Doppler echocardiogram during hospital stay noted a potential confounder- why? Surely all HF patients will have an objective assessment.

Results were displayed appropriately in table with main point summarised in text. Please amend Table 4 as "degree of urbanisation" data is repeated. I am unsure of the value of SI table. Also please refer to S1 figure in main text to ensure reader knows to access the information. It is important to ensure clear land marking of the supplementary material.

Results inform conclusions that travel time and urbanisation had no effect on processes of care and outcomes. Cardiology visits were more frequent among rural patients. It would have been interesting to hear your thoughts on how this will change in the future in light of declining health resources and a growing elderly population with multiple comorbidities.

Reviewer #2: Dear authors

Please find my remarks / suggestions on your publication 'Are degree of urbanisation and travel times to healthcare services associated with the processes of care and outcomes of heart failure? A retrospective cohort study based on administrative data'.

General remark: authors assume that readers have knowledge how local health care is organised. Despite they tried to optimally explain the organisation, it is not always evident to understand the organisation. Some questions reflect on this topic.

Sentence 63-65: Would the authors please rephrase: 'However, these studies focused mainly on patients with cancer and were carried out using very different data sources and methods, therefore more research is needed to obtain further evidence on this topic.'

Sentences 71-72: 'Also, there is a lack of evidence regarding transport accessibility measured as the actual distance between the patient's home and the healthcare facility.'

Sentences 177-180: Potential confounders: In order to minimise the potential confounding of individual characteristics on the association of urbanisation level and travel times with outcomes, we retrieved some patient baseline characteristics.

These included:

1. Demographic characteristics (age, sex and citizenship)

Sentences 388-343: In the discussion authors discussed the travel burden for elderly patients, and the fact that elderly patients often must be accompanied by their caregivers...

Reviewer: Accessibility of transport also means the easiness of getting transport. In case of elderly patients the presence of informal caregivers might be of utmost importance. The authors included 'citizenship' into the confounders. Yet, citizenship does not cover the presence / availability of informal caregivers to transport patients to a health care facility... Authors discuss the importance of family members / informal caregivers in relation to the transport.

I would like to ask the authors to add ‘presence of informal caregivers’ to the confounders and investigate / show the results of this important aspect.

Do the authors have information about the ratio of no-shows in the several urbanisation degrees. Do patients of the city less frequently have a no-show visit compared to rural patients? If patients do not visit health care facilities (due to transport issues, for example due to lacking transport support), this might be considered as a bad result, which now is not visible in the results.

Table 4 contains double information about 'degree of urbanization': please remove double information.

Sentence 349-355: Authors discuss about HF-CP and the fact that it is easier to organize HF-CP in rural area. Authors show the health care services in a map: S1 Text. Maps of the Local Healthcare Authority of Bologna, Northern Italy. For me as a reader it is not clear where HF-CP are located. The map shows several services, yet no HF-CP. Please add where HF-CP are organised.

Rural patients are receiving more follow-up visits from a cardiologist. Are cardiologists always functioning into outpatient cardiology services or do they have also consulting hours in other services? Or involved into the HF-CP? Please add this information.

Authors investigated a very local region. Do the authors have advice for other regions?

**********

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Reviewer #1: No

Reviewer #2: No

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9 Sep 2019

ACADEMIC EDITOR

We thank the Editor for the helpful comments.

1) It is acceptable that not all information on the methods is provided in the text if previously published. Still, the readers must be able to understand the methods without reading the cited paper. This means that that a short description of the according parts of the methods is required. Only citing a previous study is not sufficient.

Reply: We thank the Editor for his suggestion. We have now provided a more accurate description of the statistical methods used for confounder selection (Ln 229-34).

2) The authors include some limitations of their analysis but lack to mention all of them. The reviewers addressed some of them and they also made suggestions that can possibly not be addressed based on the administrative data set. The authors must clearly address this. In this regard, a very important shortcoming is that there is no information on the severity of HF.

Reply: We have now mentioned among the study limitations the absence of information on HF severity and other relevant information, including GP visits and presence of caregivers (Ln 334-7, 350-1, 381-5).

3) Instead of repeating findings previously mentioned as part of the discussion / conclusion, the authors should focus more on the reasons why they think that their findings are in some contrast to other findings and possibly also their expectations (a clear hypothesis would help in this regard), more thoughts about the potential clinical implications and future perspectives, considering expected changes in healthcare in the future (as in part also addressed by the reviewers). If the authors do not want to extend too much regarding length of the text, the introduction can be shortened. This particularly refers to the extensive discussion about the burden of heart failure. This is well known, mentioned in thousands of papers, and can therefore be shortened significantly.

Reply: We thank the Editor for his thoughtful suggestion. We have enhanced the conclusions to highlight the practical implications of our findings, as well as the future perspective related to health resource decline and population ageing (Ln 404-8). In particular, we argued that healthcare delivery could be optimised by prioritising quality, not only quantity of services being provided. The contrast with other findings is addressed in Ln 364-9, 374-7 and 396-8, where we discuss SES distribution, universal health coverage, multidisciplinary interventions and relatively short driving distances. Lastly, as suggested, the introduction has been shortened (Ln 49-52).

4) Please check that the references to tables and figures are correct. Suppl. text 1 is a figure. Please check that the manuscript follows the requirements of the journal regarding format, placement of tables, figures, references etc

Reply: Supplementary files have been renamed according to their content. We have also double-checked all formatting guidelines, including references and figure requirements.

REVIEWER #1

Many thanks for the opportunity to review this interesting manuscript examining the relationship between urbanisation and travel time with processes of care and heart failure outcomes. In general it was well written and structured with transparency and rigour from data to conclusion. I would like to make few comments which I would like your consideration.

Reply: We thank the reviewer for this positive comment. We hope that we have addressed adequately each of the issues she/he raised.

In terms of participant characteristics, it would have been beneficial to know NYHA class &/or the EF. This was particularly pertinent as on review of Table 1, 18 (4.3%) of rural compared to 27 (2.8) city and 22 (3.4) towns & suburbs were discharged from intensive care. Was there a difference in the "sickness" of the patients"?

Reply: Unfortunately, information on NYHA class and ejection fraction is not routinely collected in the Italian hospital discharge records. We have now mentioned this major shortcoming in the discussion (Ln 334-7).

Figure 1 demonstrated a numerous GP practices and centralised cardiology wards. Can I ask why GP visits were not recorded or included as a study outcome?

Reply: We thank the reviewer for raising this point. In Italy, most GPs use dedicated computer programmes to manage their rosters, appointments and clinical data. However, these programmes cannot be accessed by the Local Healthcare Authorities. The lack of information on GP visits has been now addressed in the discussion (Ln 381-5).

Use of Doppler echocardiogram during hospital stay noted a potential confounder- why? Surely all HF patients will have an objective assessment.

Reply: We thank the reviewer for her/his remark. Initially we included Doppler echocardiography in the analysis, but then decided to discard it because most patients with heart failure get this evaluation, as the reviewer correctly pointed out. Unfortunately, we forgot to erase this information from our previous versions of the manuscript. The text has been amended accordingly (Ln 178-9 and table footnotes).

Results were displayed appropriately in table with main point summarised in text. Please amend Table 4 as "degree of urbanisaton" data is repeated. I am unsure of the value of SI table. Also please refer to S1 figure in main text to ensure reader knows to access the information. It is important to ensure clear land marking of the supplementary material.

Reply: We thank the reviewer for noticing these inaccuracies—Table 4 has been corrected, and supplementary files have been renamed according to their content. We think that S1 Table might be of some value for those who are not familiar with multivariate statistics, that is, the simultaneous analysis of multiple outcomes. Because making ourselves clear is our priority, we would rather keep this synthesis matrix as supporting information.

Results inform conclusions that travel time and urbanisation had no effect on processes of care and outcomes. Cardiology visits were more frequent among rural patients. It would have been interesting to hear your thoughts on how this will change in the future in light of declining health resources and a growing elderly population with multiple comorbidities.

Reply: We thank the reviewer for her/his suggestion. We have enhanced the conclusions to highlight the practical implications of our findings, as well as the future perspective related to health resource decline and population ageing (Ln 404-8). In particular, we argued that healthcare delivery could be optimised by prioritising quality, not only quantity of services being provided.

REVIEWER #2

General remark: authors assume that readers have knowledge how local health care is organised. Despite they tried to optimally explain the organisation, it is not always evident to understand the organisation. Some questions reflect on this topic.

Reply: We thank the reviewer for the helpful comments. We hope that we have better clarified how healthcare services are organised in our Local Healthcare Authority.

Sentence 63-65: Would the authors please rephrase: 'However, these studies focused mainly on patients with cancer and were carried out using very different data sources and methods, therefore more research is needed to obtain further evidence on this topic.'

Reply: The sentence has been rephrased as follows: “However, this review included mainly cancer research studies relying on different data sources and variables” (Ln 58-9).

Sentences 71-72: 'Also, there is a lack of evidence regarding transport accessibility measured as the actual distance between the patient's home and the healthcare facility.'

Reply: The sentence has been rephrased as follows: “A potential limitation of these studies is the lack of information regarding transport accessibility measured as the actual distance between the patient’s home and the healthcare facility” (Ln 64-6).

Sentences 177-180: Potential confounders: In order to minimise the potential confounding of individual characteristics on the association of urbanisation level and travel times with outcomes, we retrieved some patient baseline characteristics. These included:

1. Demographic characteristics (age, sex and citizenship)

Reply: The sentence has been rephrased as follows: “We collected some patient baseline characteristics to reduce the potential source of confounding. These included: 1) Age; 2) Sex; 3) Citizenship” (Ln 172-6).

Sentences 388-343: In the discussion authors discussed the travel burden for elderly patients, and the fact that elderly patients often must be accompanied by their caregivers...

Reviewer: Accessibility of transport also means the easiness of getting transport. In case of elderly patients the presence of informal caregivers might be of utmost importance. The authors included 'citizenship' into the confounders. Yet, citizenship does not cover the presence / availability of informal caregivers to transport patients to a health care facility... Authors discuss the importance of family members / informal caregivers in relation to the transport.

I would like to ask the authors to add ‘presence of informal caregivers’ to the confounders and investigate / show the results of this important aspect.

Reply: We thank the reviewer for raising this important point. Unfortunately, the presence of informal caregivers is not reported in the Italian hospital discharge records. To the best of our knowledge, administrative data sources of many other countries also lack this information. We have now mentioned this major shortcoming in the discussion (Ln 350-1).

Do the authors have information about the ratio of no-shows in the several urbanisation degrees. Do patients of the city less frequently have a no-show visit compared to rural patients? If patients do not visit health care facilities (due to transport issues, for example due to lacking transport support), this might be considered as a bad result, which now is not visible in the results.

Reply: Unfortunately, this information is not available because our administrative databases include only visits that are booked AND provided to the patient. In Emilia-Romagna there is a regional law that should discourage no-shows, because patients that do not show up without cancellation have to pay the full patient contribution (Legge regionale 2/2016: “Norme regionali in materia di organizzazione degli esercizi farmaceutici e di prenotazioni di prestazioni specialistiche ambulatoriali” art. 23 comma 3). For this reason, it is reasonable to assume that the number of no-shows is limited in the catchment area of Bologna.

Table 4 contains double information about 'degree of urbanization': please remove double information.

Reply: We thank the reviewer for noticing the inaccuracy—Table 4 has been corrected.

Sentence 349-355: Authors discuss about HF-CP and the fact that it is easier to organize HF-CP in rural area. Authors show the health care services in a map: S1 Text. Maps of the Local Healthcare Authority of Bologna, Northern Italy. For me as a reader it is not clear where HF-CP are located. The map shows several services, yet no HF-CP. Please add where HF-CP are organised.

Reply: The HF-CP is a structured multidisciplinary care plan that promotes integration between primary and secondary care, and details essential steps in the care of patients. The GP remains the gatekeeper for the patients and coordinates with cardiologists and nurses for an easier access to consultation and counselling to improve lifestyle and optimise medication adherence. There are no specific HF-CP centres or facilities in the catchment area, because registered patients access GP practices, cardiology services or ambulatory care nursing practices in case they need medical care or counselling. All these aspects have been clarified in the Methods section (Ln 194-203).

Rural patients are receiving more follow-up visits from a cardiologist. Are cardiologists always functioning into outpatient cardiology services or do they have also consulting hours in other services? Or involved into the HF-CP? Please add this information.

Reply: We have now stated in the Methods section that cardiology follow-up visits can be provided either in inpatient cardiology services or in outpatient cardiology services (Ln 125). Cardiologists in either settings of care can see all patients with HF.

Authors investigated a very local region. Do the authors have advice for other regions?

Reply: We thank the reviewer for her/his question. Our findings cannot be generalised to isolated and remote communities, but we gave some advice for other regions where driving distances to healthcare facilities are relatively short. In particular, we argued that healthcare delivery could be optimised by prioritising quality, not only quantity of services being provided (Ln 404-8).

Submitted filename: Reply 2019.09.09.doc

Click here for additional data file.

23 Sep 2019

PONE-D-19-20409R1

Are degree of urbanisation and travel times to healthcare services associated with the processes of care and outcomes of heart failure? A retrospective cohort study based on administrative data

PLOS ONE

Dear Dr. Avaldi,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

==============================

The manuscript has significantly improved. However as suggested by both reviewers, there are minor aspects remaining which I would like you to address before your manuscript is ready for publication. Please note that PLOS ONE does not type edit accepted manuscript. This requires that manuscripts need to be in standard English and even small adjustments may be required prior to acceptance of a manuscript.

==============================

We would appreciate receiving your revised manuscript by Nov 07 2019 11:59PM. When you are ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter.

To enhance the reproducibility of your results, we recommend that if applicable you deposit your laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). This letter should be uploaded as separate file and labeled 'Response to Reviewers'.

A marked-up copy of your manuscript that highlights changes made to the original version. This file should be uploaded as separate file and labeled 'Revised Manuscript with Track Changes'.

An unmarked version of your revised paper without tracked changes. This file should be uploaded as separate file and labeled 'Manuscript'.

Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out.

We look forward to receiving your revised manuscript.

Kind regards,

Hans-Peter Brunner-La Rocca, M.D.

Academic Editor

PLOS ONE

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Dear Author,

Many thanks for the opportunity to review your revised manuscript. You have clearly and concisely addressed initial concerns, which have strengthened your submission.

Please consider the following comments which remain outstanding

Sentence 65: Please remove repetition of the words " relying on different"

Sentence 77: Change the word "founded" to "established"

Sentence 83: Remove the word "However" as not required

Sentence 86: Ensure consistency - consider rephrasing to " The objectives of this study were to investigate whether urbanisation levels and travel time to healthcare services in the LHA of Bologna, are associated with processes of care and outcomes of patients with heart failure".

Sentence 100: Could you provide details of the data sources, perhaps in a table format?

Sentence 180: Insert the word "variable" after confounding

Sentence 212: Please rephrase

Sentence 257: Consider using the term pseudonymised instead of "de-identified"

Sentence 330- Clarify there are indeed 2 tables "A" and "B" within S4

There are a number of limitations noted within the discussion section. It might be more appropriate to group these together into one paragraph, titled limitations.

Best wishes as you proceed with this submission

Reviewer #2: Thanks for your answers and for adapting the manuscript according to the comments.

I've found one sentence which has to be corected: Sentence 58-59: double text:

However, this review included mainly cancer research studies relying on different relying on different data sources and variables.

**********

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Reviewer #1: No

Reviewer #2: No

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25 Sep 2019

REVIEWER #1

Sentence 65: Please remove repetition of the words "relying on different"

Reply: We thank the reviewer for noticing this inaccuracy. The text has been amended.

Sentence 77: Change the word "founded" to "established"

Reply: The verb has been changed as suggested.

Sentence 83: Remove the word "However" as not required

Reply: We agree with the reviewer that the two paragraphs are congruent and no adverb is required to link them. The text has been amended.

Sentence 86: Ensure consistency - consider rephrasing to "The objectives of this study were to investigate whether urbanisation levels and travel time to healthcare services in the LHA of Bologna, are associated with processes of care and outcomes of patients with heart failure".

Reply: We thank the reviewer for raising this point. Our introduction is “travel time-oriented”, that is, we highlight that there is lack of evidence regarding transport accessibility measured as the actual distance between the patient’s home and the healthcare facility. We organised our study aim on purpose to give priority to travel times, and added that urbanisation was also assessed to be consistent with existing literature. We really appreciate the reviewer’s suggestion, but we feel that putting urbanisation level and travel times on the same level in the last paragraph would make the whole introduction section less flowing.

Sentence 100: Could you provide details of the data sources, perhaps in a table format?

Reply: A new supplementary table (S1) has been included, as suggested.

Sentence 180: Insert the word "variable" after confounding

Reply: In this sentence, “confounding” is a noun. A number of occurrences where “confounding” is used as a noun can be borrowed from the literature (e.g., Occup Environ Med 2003;60:227-34).

Sentence 212: Please rephrase

Reply: We have rephrased the sentence as follows: “There are no facilities specifically dedicated to the HF-CP: registered patients can access GP practices, cardiology services or ambulatory care nursing practices in case they need medical care or counselling.”

Sentence 257: Consider using the term pseudonymised instead of "de-identified"

Reply: We thank the reviewer for her or his suggestion. The verb has been changed as suggested.

Sentence 330: Clarify there are indeed 2 tables "A" and "B" within S4

Reply: This aspect has been clarified for S3, S4 and S5 Tables.

There are a number of limitations noted within the discussion section. It might be more appropriate to group these together into one paragraph, titled limitations.

Reply: We agree with the reviewer that grouping together all limitations in a single paragraph might be desirable. The journal gives a degree of freedom to the authors, who are not forced to fill prearranged sections when writing the papers. We took advantage of this to write a discussion where methodological pitfalls are in the focus. The reviewer can see that a number of important limitations, such as the lack of relevant clinical information, are at the very beginning of the discussion—the editor asked us to give much relevance to such limitations. For this reason, we have kept the discussion unchanged, but added a subsection where all limitations are now summarised.

REVIEWER #2

I've found one sentence which has to be corrected: Sentence 58-59: double text: “However, this review included mainly cancer research studies relying on different relying on different data sources and variables.”

Reply: We thank the reviewer for noticing this inaccuracy. The text has been amended.

Submitted filename: Reply 2019.09.25.doc

Click here for additional data file.

1 Oct 2019

Are degree of urbanisation and travel times to healthcare services associated with the processes of care and outcomes of heart failure? A retrospective cohort study based on administrative data

PONE-D-19-20409R2

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21 Oct 2019

PONE-D-19-20409R2

Are degree of urbanisation and travel times to healthcare services associated with the processes of care and outcomes of heart failure? A retrospective cohort study based on administrative data

Dear Dr. Avaldi:

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on behalf of

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