Introduction

Medical science has advanced rapidly since the early 19th century. Major advances from the germ theory to the sequencing of the human genome have together generated much deeper understanding of the pathophysiology of disease with improved prevention and treatment. However, all these advances are mostly related to physical factors. Research on human aspects of medical care has lagged.

Internationally, there has been a decrease in the perceived value of personal contact between patients and doctors. An editorial in the New England Journal of Medicine 1 suggested that non-personal care should become the ‘default option’ in medicine.

One way to study interpersonal care is by measuring continuity of care. The definition of continuity of care that we have used previously2 is repeated contact between an individual patient and a doctor. Such repeated contact gives patients and doctors the opportunity for improved understanding of each other’s views and priorities. Continuity of care can be considered to be a proxy measure for the strength of patient–doctor relationships.3

There have been a variety of approaches to measure continuity and so far only three randomised controlled trials have been completed.4–6 These all showed continuity to be beneficial for patients over relatively short periods. However, RCTs are problematic with pre-existing long-term human relationships, like marriage and parent–child relationships, as prospective randomisation is almost impossible. Some doctor–patient relationships last for decades and become highly personal, and therefore RCTs are unethical or impractical. Observational studies have inherent limitations, and investigating continuity of care has certain problems, in particular that of reverse causality; poor health or death early in the study leading to a low measured level of continuity.7 However, study teams are increasingly aware of this and use study designs and analytical methods to reduce and account for it.

There is a clear rationale for the effectiveness of continuity of care as doctors collect ‘accumulated knowledge’8 about an individual patient which they then use in subsequent consultations to tailor advice.

Continuity of care in general practice is associated with greater patient satisfaction,9 improved health promotion,10 increased adherence to medication11 and reduced hospital use.12 Given all these separate benefits, the question arises whether these extend to mortality rates. Death is clearly the most important and serious of all outcomes.

Since 2010, individual studies have emerged investigating whether continuity of care is associated with reduced mortality, including some with specialists.13–35 These reports represent a new development, underlining the interpersonal component of medical care.

Research question

Are higher levels of continuity of doctor care, in any setting, with any patient group, associated with changed mortality?

Methods

Search strategy and selection criteria

For inclusion in this systematic review (without meta-analysis), articles must have been published in the peer-reviewed literature, in the last 21 years, in English. We searched the databases of MEDLINE, Embase and the Web of Science from 1996 to 2017 by searching for ‘continuity’ OR ‘continuity of care’ together with terms for a medical doctor/physician and terms indicating death or mortality in the title or abstract (see online supplementary information—example search strategy). In addition, references of articles selected were hand-searched for additional relevant citations.

Supplementary file 1

Experimental and observational study designs were considered including controlled trials, cohort studies (prospective and retrospective) and case–control studies. Systematic reviews and meta-analyses were excluded. Study participants could include any patient group, including entire populations or groups of patients with a specific disease or other feature.

Articles must have compared measured degrees of continuity of care with doctors (of any kind) to mortality rates. Any valid measure of continuity was considered, including continuity being lost or absent and articles where the continuity measure was a single appointment or visit by a general practitioner/family physician during a hospital stay. Articles about organisational continuity and general staffing numbers were excluded.

As an outcome measure, any measure of mortality was accepted, that is, all-cause, time/age-limited or cause-specific. When complications or hospital admissions were combined with death rates, we sought a separate measure of mortality alone. If this was not available, studies were excluded.

Two pairs of reviewers checked the search results and decided independently whether papers met the eligibility criteria. Initially, the title and abstract of each citation was screened. The full texts of selected articles were then examined. Disagreements were resolved by discussion, and PHE independently had the deciding vote.

Data items

The variables and outcomes extracted included basic information: authors, date and country. We also extracted study design, study population (any particular condition, setting, age group, any other inclusion or exclusion criteria and selection method), numbers of patients, measure of continuity, length of continuity measurement and doctor type (generalist doctor including general practitioner, family physician and primary care physician or specialist). We extracted the period of time for the mortality measurement, and any overlap with or interval between mortality and continuity measurement periods. We also extracted whether mortality was all-cause or a disease-specific cause or limited to a particular group, how mortality was assessed and confounding factors tested or accounted for. We also extracted an estimation of any association found, with risk ratio or OR where possible and whether higher continuity was linked to an increased or decreased mortality risk. Data were extracted independently by two reviewers (of DJPG, EW, AT and KSL), using the data-extraction table designed for this review. Disagreements were resolved as described previously.

Risk of bias

The quality and risk of bias were assessed independently for individual studies by two reviewers using the Newcastle-Ottawa Scale.36 We also assessed relevant areas of bias in terms of the timing of continuity and mortality measurement and confounding factors considered. For continuity of care and mortality, there is a particular potential for bias in that the worsening of health status before death may cause either decreased or increased continuity of care (reverse causality),7 so we noted whether this had been considered and adjusted for in study design. In terms of bias across studies, we considered publication bias and reporting bias in terms of whether mortality was the primary outcome.

Data analysis

Studies were analysed for a relationship between continuity of care and mortality rates, and whether this relationship was an inverse one (ie, greater continuity of care led to lower mortality rates) or not. For each study, we sought a risk metric (ie, relative risk ratio, HR or OR) from an adjusted model of data analysis in order to minimise the risk of selection bias and confounding. Where these statistical metrics were not reported, we provided any other available comparison measure.

Patient involvement statement

DJPG is a member of the St Leonard’s Practice Patient Participation Group as well as the Patron of the National Association for Patient Participation. As such, he is a patient representative as well as an author. The research question and outcomes were therefore conceived by a patient from the practice based on the priorities, experience and preferences stated by patients at successive national patient conferences.

Results

Study selection

After removal of duplicate results, 726 peer-reviewed publications were identified. No previous systematic reviews or trials on this subject were found. Of the 726 papers identified, 43 papers were selected for full-text review (figure 1). Articles were then excluded if continuity was not clearly measured or was the dependent variable,37–42 if the continuity of care measure was not clearly with a doctor or doctors only35 43–49 and if mortality was not analysed or not analysed separately at any point50–52 (eg, if it was expressed only as a composite outcome with hospitalisation). This left 22 studies for inclusion.

Figure 1

Figure 1

 

Figure 1

Study selection flow diagram.

Study characteristics

As shown in table 1, the majority of included reports (15, 68.2%) were of retrospective cohort studies, often using insurance data. There were four prospective cohort and three cross-sectional studies. No randomised controlled trials were found. A number of cohort studies included large numbers of patients (median 16 855). All of the reports were published since 2010. The studies were carried out in nine different countries; the majority were from North America (Canada 6, USA 5). Seven were from Europe (England 3, France 2, Croatia 1 and the Netherlands 1). There were two from Taiwan and one each from Israel and South Korea.

Table 1

Studies investigating the link between continuity and mortality that meet the inclusion criteria, ordered by study design

Nine (40.9%) of the studies investigated continuity with a general practitioner/family physician/primary care physician, 3 were with specialists only17 19 20 and 10 included continuity with doctors of any kind. Eight studies (34.8%) selected patients during or following an index hospitalisation.15–18 20 25 26 29. Five studies studied patients with diabetes22 23 27 30 31 and three studies focused on older patients.13 24 31

The continuity measures used are reported in table 1. The most common measure used was the Usual Provider of Care (UPC) index which was used in 10 studies (45.5%).13 16 17 21 23 25 26 29–31 Six studies used more than one measure, some only for sensitivity analysis.13 21 25 26 28 29 One study13 was designed to compare the association of different continuity measures with outcomes, including mortality. One article18 used the occurrence of a supportive visit by a family physician to a patient in hospital and another14 simply took loss of contact as meaning loss of continuity. Three studies32–34 used the results of a question or questions from the annual UK national General Practice Patient Survey.

The length of time over which continuity was measured (when not a survey response or hospital visit indicating a relationship) varied greatly between studies, from a single weekend in hospital17 up to 17 years.24 The median length of continuity measurement was 2 years (IQR 3.75).

Most studies (20, 90.9%) reported all-cause mortality. One study32 investigated premature mortality; under the age of 75. Another33 used premature coronary heart disease mortality as the primary outcome. The length of time for recording deaths also showed a large variation between studies, from 30 days to up to 21 years. The median follow-up time was 2.5 years (IQR 4.4).

Most of the studies investigated a large number of potential confounding factors (table 1). All studies working at the level of individual patients included some measure of health status including LACE index, comorbidities, previous healthcare usage and other measures. Most studies looked at age and sex and 14 (63.6%) used a measure of deprivation, social status or income.

Results of individual studies

Of the 22 studies, 18 (81.8%) showed that greater continuity of care was significantly associated with lower mortality. Of these, 16 (72.7% of the 22) were with lower all-cause mortality (table 2). Two studies found no association of greater continuity of care with subsequent mortality during17 or following16 a hospital stay. One study found that continuity was not significantly associated with mortality except in general practices in the least deprived areas.32 One study13 investigated a range of continuity measures. They found that all insurance claims-based measures showed that higher levels of continuity were associated with higher mortality rates but greater continuity as reported by patients was associated with reduced mortality. This is the only study showing any association of increased continuity with increased mortality.

Table 2

Outcome measures of studies investigating the association of continuity of care with mortality

Due to the heterogeneity of study continuity and mortality measurements, it was not possible to combine them to produce an estimate of effect size; however, table 2 shows the risk ratio, OR or HR from individual studies where available.

Risk of bias within studies

Using the Newcastle-Ottawa Scale,36 all 22 studies were rated as high quality, with nine 10 studies (40.9%) gaining maximum scores from both reviewers independently (table 1, supplementary table). No study was scored less than 7 out of 9 by any reviewer. As all these studies were cohort or cross-sectional studies, they tested for associations only. However, most involved statistical analyses for a wide range of potential confounding factors (table 1).

The specific bias of reverse causality between the healthcare-related events that might occur before death was discussed in 14 (63.6%) of the studies. Four cohort studies did not discuss reverse causality.14 24 27 31 However, all of the studies included some measure of health/disease status as a potential confounding factor and some included several detailed measures of these in their models.

Five of the studies had a design which meant there was no overlap between the time for continuity measurement and the period during which deaths were counted.13 20 22 28 30 Seven studies have complete14 16 21 23 28 29 31 and four partial overlap of these periods.17 19 24 25 Five studies included additional analyses which either eliminated the overlap23 or introduced a lag time19 21 26 28 between continuity and mortality measurement periods. In each of these additional analyses, continuity was still found to be significantly associated with mortality. One long-term study24 calculated survival from the date of the last continuity measurement and stratified by the length of time in the study. Five studies19 21 25 28 29 used their continuity score as a time-dependent variable in the model.

Risk of bias across studies

There is a risk of publication bias. It may be that reports showing no effect are less likely to be published. However, two showed no association. In two, mortality was not the primary outcome and in six, it was part of a composite outcome. For 13 studies, mortality was not the only outcome. In 10 studies, the association of two or more factors, including doctor continuity of care, with outcomes was tested. Continuity and mortality as exposure and outcome, respectively, are reported in a range of studies, including where testing this association was not the primary aim.

Discussion

Principal findings

In a substantial majority of studies (18, 81.8%) meeting the selection criteria, higher levels of continuity of care with doctors were associated with lower mortality rates. Two others, finding no significant association, had very short timescales for measurement of continuity, to the extent that the strength of any patient–doctor relationship was potentially questionable. Another study showing no significant association with all-cause mortality was cross-sectional, and the measurement methods related to questions on a national survey about seeing a particular general practitioner, again not necessarily indicative of a strong patient–doctor relationship.

One study8 found that for claims-based measures of continuity, increased mortality was associated with higher levels of continuity of care. However in the same study, higher levels of patient-reported continuity were associated with lower mortality rates. This emphasises the interpersonal relationship between patient and doctor as claims-based measures only give numbers of contacts and do not directly measure the quality of the relationship.

The effect sizes were generally small (table 2) but these were in the same range as some treatment effects, as very large, repeatable effects on mortality are rare.53 In addition, for some studies included in this review, effect sizes were calculated using very small increments in the continuity measure.

Strengths and weaknesses of the evidence

All the studies found investigating the association of continuity of care with mortality were observational in nature, although the majority were high-quality cohort studies including three prospective cohort studies. The issue of reverse causality applies to all the evidence presented here. This could bias an association between continuity of care and mortality in either direction. As patient health worsens when approaching death, continuity of care may deteriorate for many reasons, for example, patients moving areas to accommodate increased health needs, the need to see more specialists or a loss of ability to obtain and attend appointments. Alternatively, deterioration of health could lead to a concerned doctor ensuring that the patient receives more continuity of care. For the cross-sectional studies, there is also a potential for confounding due to practice-level factors.

There have been randomised controlled trials into continuity of care but none on existing relationships or lasting longer than a year and none with mortality as an outcome.4–6 Observational studies which control rigorously for confounding factors and have a design aimed at limiting the impact of reverse causality are the best evidence available.

Of the 16 cohort studies finding an association of higher continuity with lower mortality, most studies attempt to at least partially account or control for reverse causality in their study design or analysis. Most controlled for differences in health status and risk factors. Some carried out analyses measuring continuity and mortality in separate years, or with a lag. This method, particularly the lag between measurements, should help to minimise bias caused by rapid worsening prior to death. However, four cohort studies showing this association14 24 27 31 did not discuss this kind of reverse causality although one24 nevertheless made several adjustments for health status and calculated survival from the date of the last continuity measurement. Measuring continuity and mortality over separate time periods is also one way of eliminating the potential bias caused by those who survived longer having more time to accrue continuity (time-dependent bias). Another way of reducing this is to model continuity as a time-dependent variable which was the case in five studies.19 21 25 28 29

All studies included were rated as high quality, using the Newcastle-Ottawa Scale.

Several of the articles reported on studies using very large cohorts. The studies came from a number of different countries with different healthcare systems and cultures. Continuity of care in the studies included that received from specialist as well as generalist doctors, showing that the effect is not limited to one branch of medicine or health system.

As continuity research is an emerging field, no consensus on the best way to measure it has been reached. The measure used most was the UPC Index which does not take into account the total number, frequency or sequence of visits.54

Doctors have been studied as a discrete category in numerous studies, and data systems usually allow them to be separately studied. The group studied included family doctors/general practitioners, physicians and psychiatrists so was already heterogeneous so expanding this to other professional groups would have complicated interpretation. As doctors are the most highly trained health professionals with the most influence over decisions, it is reasonable to assume that if interpersonal contact affects mortality, it is most likely to occur with doctors. Therefore, we eliminated articles, some with significant reductions in mortality, that measured continuity in relation to mixed profession teams or to other health professionals.35 43–49 This is the first systematic review investigating whether continuity of doctor care is associated with reduced mortality. We expect this to encourage studies with different selection criteria; for example, for continuity with other healthcare professionals.

Possible mechanisms and implications

This review, finding that increased receipt of continuity of care is associated with reduced mortality, comes after it has been shown that continuity of care is associated with multiple benefits for patients.9–12 It therefore fits well with such earlier work. It is only recently that large databases and long-term cohort studies have made effective investigation into the links between continuity and mortality possible.

These known associations suggest possible mechanisms in that greater uptake of evidence-based preventative medicine such as immunisations as well as better concordance with treatments is likely to reduce mortality. Continuity of care is associated with patients perceiving that the doctor has become more responsive.55Patients then disclose more and medical management is more likely to be tailored to the needs of the patient as a person. The increased patient satisfaction may also be associated with an ‘optimism’ boost to health.56 We have previously suggested that ‘doctors tend to overestimate their effectiveness when consulting with patients they do not know, and underestimate their effectiveness when consulting with patients they know’.57

The cumulative impact of these multiple gains may then be reflected in reduced mortality.

Historically, continuity of care has been considered a feature of the practice of medical generalists and featured in the job descriptions of the general practitioner.58 59 Recent studies included in this review found that continuity was associated with reduced mortality with specialist physicians,22 28 psychiatrists19 and surgeons20 too.

Although this evidence is observational, with 18 of the 22 studies showing significant reductions in mortality with continuity of doctor care, the clear preponderance of evidence is in favour of the association. Three studies showed no significant association and one13 had mixed results but no study exclusively showed an association of higher continuity of care with higher mortality rates. Although there are difficulties in carrying out controlled trials on this subject, a few, with interventions to increase continuity of care, have been successful,4–6 and this could be attempted more widely. The presence of this association in nine countries, across three continents, and in very different populations and healthcare systems implies a basic human effect.60 The policy implication as many studies noted is prioritising continuity of care.

For 200 years, medical advances have been mainly technical and impersonal which has reduced attention to the human side of medicine. This systematic review reveals that despite numerous technical advances, continuity of care is an important feature of medical practice, and potentially a matter of life and death.

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