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Continuity of care (COC) has been defined as seeing the same health care provider over time, and is one of the four main domains of primary care.1 Continuity of care presupposes the existence of a regular source of care over time, regardless of the presence or absence of disease or injury. It is intended to help the provider and the patient build a long-term relationship in order to foster mutual trust between provider and patient, and knowledge of both parties' expectations and needs.2Studies, mainly from the US, have shown that increased continuity of care is associated with positive health outcomes,3 high quality care,4 better medication and appointment compliance, enhanced physician recognition of the patient's health needs, 5and high patient satisfaction with the care.6,7 Research has also suggested that having a regular and consistent source of care is associated with lowering health care costs 3 by decreasing use of emergency services8,9 and hospitalisations,10,11 particularly for ambulatory-care-sensitive conditions (conditions that are more amenable to primary care interventions).The hypothesized benefits of continuity of care with a primary care provider (PCP) are based on the accrued mutual knowledge, trust and communication between patients and providers that arises from repeated contact.1-3 Hence, there is considerable policy interest in defining the characteristics of people who receive continuity of care from their PCPs.While the benefits of continuity of care with a primary care provider are well documented, relatively little is known about those patients who receive continuity of care. Studies which have looked at patients who did not receive continuity of care noted that they were typically younger, female and had relationship problems.12,13 Our goal in this study is to construct a summary measure of continuity of care and to enhance understanding of the prevalence of continuity of care in New Zealand (NZ).While defining the characteristics of those who receive continuity of care is of interest in its own right, it is particularly important in the NZ context, mainly because the different attributes of primary care have not been studied to the same extent as in countries such as the US, leading to a paucity of evidence that grounds the NZ experience in the international context. Moreover, studies from the US mainly focus on a single State, clinic/provider or hospital, or non-elderly population thus restricting the generality of the results.Other studies focus on continuity of care at the level of the whole system, rather than at an individual patient level. This may, in part, be due to the challenge of collecting information at the individual level about aspects of primary care, or the inability of consumers to be valid judges of primary care quality.14This study extends the current literature on continuity of care by using a large national survey and by including a variety of demographic, socioeconomic, health behaviour and health variables. We hypothesise that those who have greater need for care will experience a higher mean continuity of care score.MethodsData This research used SoFIE-Health data, which is part of the Statistics New Zealand-led Survey of Family, Income and Employment (SoFIE). SoFIE is a single fixed panel and is the largest longitudinal survey ever run in New Zealand. It is a nationally representative study of about 22,000 adults, drawn by random sampling of households, interviewed face-to-face. All adults in the original sample are followed for a maximum duration of eight years starting from October 2002, even if their household or family circumstances change. It collects information once a year from the same individuals on income levels, sources and changes; together with the major influences on income such as employment and education experiences, household and family status and changes, demographic factors and health status. The SoFIE-Health module is comprised of 20 minutes of questionnaire time in waves 3 (2004-05), 5 (2006-07) and 7 (2008-09), in the following health-related domains: SF-36 (Short-Form health survey), Kessler-10 (K-10), perceived stress, chronic conditions (heart disease, diabetes, and injury-related disability), tobacco smoking, alcohol consumption, health care utilisation, access and continuity of primary health care, and an individual deprivation score. The health module is administered to the original sample members (OSM). Main outcome variable The main outcome measure used for this work was an index of continuity of care which is assessed by the following four questions in SoFIE-Health. Q1: Would the same doctor or nurse take care of you every time you go? Q2: If you called them, could you talk to the person that knows you best? Q3: Do you think they know you very well as a person? Q4: Do you think they know what medical problems are most important to you? The response categories include definitely, probably, probably not and definitely not and are coded/scored as 4,3,2,1 respectively so that a higher total score indicates higher continuity of care. We based our method on the Primary Care Assessment Tools (PCAT) in order to translate the concept of continuity of care into characteristics that can be measured.15,16 The Primary Care Assessment Tools were developed to collect and analyse information needed to describe primary care services needed, provided and experienced by the population. Following PCAT, we excluded those individuals who refused to answer any of Q1 - Q4 above. Individuals who responded "not sure, don't remember" to more than 2 questions were also excluded. For those who responded "not sure, don't remember" to only one of the 4 questions, we replaced "not sure, don't remember" with "probably" The mean continuity of care score for an individual was calculated by summing the score of the four questions for each individual and dividing this sum by the number of questions (4 in this case). For a detailed example of the creation of the score, see Jatrana et al (2008a).17 Independent variables We included sociodemographic, health risk behaviour and health status variables as covariates. Independent variables chosen for analyses were based on our review of the literature and our research questions served as a guide in the selection of variables to include in the model of continuity of primary care. Sociodemographic variables in this analysis are age, gender, marital status, ethnicity, family structure, household equivalised income, labour force status, highest level of education achieved, NZDep (area deprivation), and NZiDep (individual deprivation). Health behaviour and health included current smoking status, Kesseler-10 and number of chronic conditions. Categories for the various measures are shown in Table 1. A description of these variables is as follows: Age—Age was calculated at the Wave 3 interview date and categorised into the following age groups: 15-24, 25-44, 45-64, and 65+. Ethnicity—This paper uses the ‘prioritised' concept of ethnicity. With the ‘prioritised' concept, each respondent was assigned to a mutually exclusive ethnic group by means of a prioritisation system commonly used in New Zealand: Māori, if any of the responses to self-identified ethnicity was Māori; Pacific, if any one response was Pacific but not Māori; Asian, if any one response was Asian but not Māori/Pacific; the remainder non-Māori non-Pacific non-Asian (nMnPnA). The nMnPnA category mostly comprises New Zealanders of European descent, but strictly speaking is not an ethnic group. Marital status—Marital status relates to legal marital status and is categorised into currently married, previously married (separated/porced/widowed) and never married. NZDep2001—NZDep2001 is a census-based small-area index of socioeconomic deprivation [24]. The Deprivation index score of dwelling location is derived from NZDep and assigned to the small area of the dwelling. NZDep2001 deprivation scores apply to areas rather than individual people. The index scale used here is from 1 to 5, where 1 = the least deprived 20% of areas and 5 = the most deprived 20% of areas. NZiDep—The NZiDep index is a tool for measuring socioeconomic deprivation for individuals and is based on eight simple questions which take about 2 minutes to administer [25]. The final deprivation score was coded into the following five ordinal categories. Relatively few people have the largest number of deprivation characteristics. 1 = no deprivation characteristics 2 = one deprivation characteristic 3 = two deprivation characteristics 4 = three or four deprivation characteristics 5 = five or more deprivation characteristics Income—In SoFIE, income is collected from every individual over 15 years at every wave. Household income was derived by totalling adult annual personal income (before tax) from all sources received, consumer price index (CPI) adjusted for the quarter ending December 2001 (the first reference quarter of the study), equivalised for household economies of scale using a NZ-specific equivalisation index [26], and categorized into tertiles: low (<$26,109), medium ($26,109 to $43,015) and high (≥$43,016). For the analyses in this paper, equivalised household income at wave 1 was used. Education—The education variable used in this analysis was the highest level of education at Wave 3, categorised as no qualification, school qualification, and post-school qualification. Smoking—A current smoking status variable was created from responses to questions "Do you smoke cigarettes", and "Have you ever been a regular smoker" and is coded into three categories: current smoker, ex-smoker and never smoker. Kessler-10 scale—The Kessler-10 (K-10) is a scale measuring non-specific psychological distress [27, 28]. The K-10 consists of ten questions about non-specific psychological distress and seeks to measure the level of current anxiety and depressive symptoms based on questions about negative emotional states a person may have experienced in the four weeks prior to interview. The scores were grouped into four levels according to the criteria developed by Andrews and Slade (2001): low (10-15), moderate (16-21), high (22-29), and very high (30+) [29, 30]. Chronic diseases—As part of the health module each respondent was asked "have you ever been told by a doctor that you had": Asthma, High Blood Pressure, High Cholesterol, Heart Disease, Diabetes, Stroke, Migraines, Chronic Depression, Manic Depression or Schizophrenia. These data were coded into a co-morbidities index: 0, 1-2, >2 co-morbid diseases. Statistical analysis This paper provides cross-sectional analyses of wave 3 data. The sample used in the analyses consist of 18,320 adult (15 years and above) OSMs. Analyses were carried out using means and 95% confidence intervals (CI) to evaluate the bivariate associations between continuity of care scores and other variables. Ordinary Least Square (OLS) regression was used to adjust for covariates, including age, sex, marital status, ethnicity, household equivalised income, labour force status, small area deprivation, individual deprivation, education, smoking and health (self-assessed health, K-10 and number of chronic conditions). The population used in the regression analyses was 11,915 adult OSMs at wave 3 who had complete information on all the socioeconomic, health behaviour and health characteristics. All counts presented in this paper are random rounded (up or down) to the nearest multiple of 5, with a minimum value of 10, as per the Statistics New Zealand confidentiality protocol. All analyses were performed on unit level data using SAS version 8.2 within the Statistics New Zealand data laboratory. Results Table 1 presents the associations between mean continuity of care scores and demographics, socioeconomic, health and health behaviour characteristics of the respondents. The mean score for continuity of care was 3.10 (95%CI: 3.09-3.11) with a range of 1.0-4.0. As the age of the respondents increased, so did the mean continuity of care score, with older respondents aged 75 and above reporting a mean score of 3.48 (95%CI: 3.45-3.51) as compared to younger respondents aged 15-24 (2.86, 95%CI: 2.83-2.89). There was little variation in the mean score for continuity of care with respect to sex, however, sex CIs do not overlap. Statistically significant variability of continuity of care was also observed for marital status and ethnicity. Income was negatively associated with continuity of care score. For example, those in the lowest income tertile had a mean continuity of care score of 3.23 (95%CI: 3.21-3.25) and those in the highest income tertile had a mean continuity of care score of 3.02 (95%CI: 3.00-3.04). Statistically significant variability of continuity of care was observed for labour force status: those not working had a higher mean continuity of score (3.24, 95%CI: 3.22-3.26) as compared to those who were working (3.02, 95%CI: 3.01-3.03). There was little evidence for significant variation of continuity of care with NZDep, NZiDep, or education. In contrast, significant variability was observed for the smoking covariate. Table 1. Demographic, socioeconomic and health characteristics of study population by mean continuity of care score: SoFIE-Health, 2004-051 Characteristics N Mean (95%CI) All 16630 3.10 (3.09-3.11) Age 15-24 2255 2.86 (2.83-2.89) 25-44 5550 2.95 (2.93-2.97) 45-64 5725 3.17 (3.15-3.19) 65-74 1695 3.38 (3.35-3.41) 75+ 1400 3.48 (3.45-3.51) Sex Male 7365 3.07 (3.05-3.09) Female 9270 3.13 (3.12-3.14) Marital status Currently married 8980 3.16 (3.15-3.17) Previously married 3020 3.24 (3.22-3.26) Never married 4625 2.91 (2.89-2.93) Ethnicity NZ/European 13160 3.11 (3.10-3.12) Māori 1780 3.01 (2.98-3.04) Pacific 695 3.20 (3.15-3.25) Asian 725 3.11 (3.06-3.16)

Summary

Abstract

Aim

Method

Results

Conclusion

Author Information

Acknowledgements

Correspondence

Correspondence Email

Competing Interests

Starfield B. Primary Care: Concept, Evaluation, and Policy. New York: Oxford University Press, 1992.Blumenthal D, Mort E, Edwards J. The efficacy of primary care for vulnerable population groups. Health Services Research 1995;1995(30):253-273.Weiss LJ, Blustein J. Faithful patients: The effect of long-term physician-patient relationships on the costs and use of health care by older Americans. American Journal of Public Health 1996;86(12):1742-1747.Christakis DA, Wright JA, Zimmermann FJ, et al. Continuity of care is associated with high quality care by parental report. Pediatrics 2002;109(4):e54-e59.Becker MH, Drachman RH, Krischt JP. Continuity of pediatrician: new support for an old shibboleth. Journal of Paediatrics and Child Health 1974;84:599-605.Hjortdahl P, Borchgrevink CF. Continuity of care: influence of general practitioners' knowledge about their patients on use of resources in consultations. British Medical Journal 1991;303:1181-1184.Wasson JH, Sauvigne AE, Mogielnicki RP. Continuity of outpatient medical care in elderly men: a randomized trial. JAMA 1984;252:2413-2417.Christakis DA, Wright MD, Koepsell TD, Emerson S, Connell FA. Is greater continuity of care associated with less emergency department utilization? Pediatrics 1999;103(4):738-742.Gill JM, Mainous AG, Nsereko M. The effect of continuity of care on emergency department use. Archives of Family Medicine 2000;9:333-338.Gill JM, Mainous AG. The role of provider continuity in preventing hospitalizations. Archives of Family Medicine 1998;7:352-357.Mainous AG, Gill JM. The importance of continuity of care in the likelihood of future hospitalization: Is site of care equivalent to a primary clinician? American Journal of Public Health 1998;88(10):1539-1541.Gray DJP. The key to personal care. Journal of Royal College of General Practitioner 1979;29:666-678.Sweeney KG, Gray DP. Patients who do not receive continuity of care from their practitioner - are they a vulnerable group? British Journal of General Practice 1995;45:133-135.Bindman AB, Grumbach K, Osmond D, et al. Primary care and receipt of preventive services. Journal of General Internal Medicine 1996;11(5):269-76.Shi L, Starfield B, Xu J. Validating the adult Primary Care Assessment Tool. Journal of Family Practice 2001;50:161-175.Starfield B, Cassady CE, Nanda JP, et al. Consumer experiences and provider perceptions of the quality of primary care: implications for managed care. Journal of Family Practice 1998a(46):3.Jatrana S, Crampton P, Carter K, et al. SoFIE-Health Primary Care: Overview and Early Results: University of Otago, Wellington, 2008a.Carter K, Hayward M, Richardson K. SoFIE-Health Baseline Report: Study Design and Associations of Social Factors and Health in Waves 1 to 3. SoFIE-Health Report 2 University of Otago, Wellington, 2008.Hauck K, Rice N. A longitudinal analysis of mental health mobility in Britain. Health Economics 2004;13:981-1001.Watson N, Wooden M. The HILDA survey four years on. Australian Economic Review 2004;37:343-9.Forrest C, Starfield B. The effect of first-contact care with primary care clinicians on ambulatory health care expenditures Journal of Family Practice 1996;43:40-48.Deutchman ME, Sills D, Connor PD. Perinatal outcomes: a comparison between family physicians and obstetricians. Journal of American Board of Family Practice 1995;8:440-447.Jatrana S, Crampton P. Affiliation with a Primary Care Provider in New Zealand: Who is, Who isnt. Health Policy 2009;91:286-296.Barnett R. \"Wait till it's serious\": health care costs and urban survival strategies of low income groups in Christchurch. New Zealand Medical Journal 2000;113:350-354.Barnett R, Coyle P. Social inequality and general practitioner utilisation: assessing the effects of financial barriers on the use of care by low income groups. New Zealand Medical Journal 1998;111:66-70.Malcolm L. Inequities in access to and utilisation of primary medical care services for M ori and low income New Zealanders. New Zealand Medical Journal 1996;109:356-358.Jatrana S, Crampton P. Primary health care in New Zealand: Who has access? Health Policy 2009b;93(1):1-10.

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Continuity of care (COC) has been defined as seeing the same health care provider over time, and is one of the four main domains of primary care.1 Continuity of care presupposes the existence of a regular source of care over time, regardless of the presence or absence of disease or injury. It is intended to help the provider and the patient build a long-term relationship in order to foster mutual trust between provider and patient, and knowledge of both parties' expectations and needs.2Studies, mainly from the US, have shown that increased continuity of care is associated with positive health outcomes,3 high quality care,4 better medication and appointment compliance, enhanced physician recognition of the patient's health needs, 5and high patient satisfaction with the care.6,7 Research has also suggested that having a regular and consistent source of care is associated with lowering health care costs 3 by decreasing use of emergency services8,9 and hospitalisations,10,11 particularly for ambulatory-care-sensitive conditions (conditions that are more amenable to primary care interventions).The hypothesized benefits of continuity of care with a primary care provider (PCP) are based on the accrued mutual knowledge, trust and communication between patients and providers that arises from repeated contact.1-3 Hence, there is considerable policy interest in defining the characteristics of people who receive continuity of care from their PCPs.While the benefits of continuity of care with a primary care provider are well documented, relatively little is known about those patients who receive continuity of care. Studies which have looked at patients who did not receive continuity of care noted that they were typically younger, female and had relationship problems.12,13 Our goal in this study is to construct a summary measure of continuity of care and to enhance understanding of the prevalence of continuity of care in New Zealand (NZ).While defining the characteristics of those who receive continuity of care is of interest in its own right, it is particularly important in the NZ context, mainly because the different attributes of primary care have not been studied to the same extent as in countries such as the US, leading to a paucity of evidence that grounds the NZ experience in the international context. Moreover, studies from the US mainly focus on a single State, clinic/provider or hospital, or non-elderly population thus restricting the generality of the results.Other studies focus on continuity of care at the level of the whole system, rather than at an individual patient level. This may, in part, be due to the challenge of collecting information at the individual level about aspects of primary care, or the inability of consumers to be valid judges of primary care quality.14This study extends the current literature on continuity of care by using a large national survey and by including a variety of demographic, socioeconomic, health behaviour and health variables. We hypothesise that those who have greater need for care will experience a higher mean continuity of care score.MethodsData This research used SoFIE-Health data, which is part of the Statistics New Zealand-led Survey of Family, Income and Employment (SoFIE). SoFIE is a single fixed panel and is the largest longitudinal survey ever run in New Zealand. It is a nationally representative study of about 22,000 adults, drawn by random sampling of households, interviewed face-to-face. All adults in the original sample are followed for a maximum duration of eight years starting from October 2002, even if their household or family circumstances change. It collects information once a year from the same individuals on income levels, sources and changes; together with the major influences on income such as employment and education experiences, household and family status and changes, demographic factors and health status. The SoFIE-Health module is comprised of 20 minutes of questionnaire time in waves 3 (2004-05), 5 (2006-07) and 7 (2008-09), in the following health-related domains: SF-36 (Short-Form health survey), Kessler-10 (K-10), perceived stress, chronic conditions (heart disease, diabetes, and injury-related disability), tobacco smoking, alcohol consumption, health care utilisation, access and continuity of primary health care, and an individual deprivation score. The health module is administered to the original sample members (OSM). Main outcome variable The main outcome measure used for this work was an index of continuity of care which is assessed by the following four questions in SoFIE-Health. Q1: Would the same doctor or nurse take care of you every time you go? Q2: If you called them, could you talk to the person that knows you best? Q3: Do you think they know you very well as a person? Q4: Do you think they know what medical problems are most important to you? The response categories include definitely, probably, probably not and definitely not and are coded/scored as 4,3,2,1 respectively so that a higher total score indicates higher continuity of care. We based our method on the Primary Care Assessment Tools (PCAT) in order to translate the concept of continuity of care into characteristics that can be measured.15,16 The Primary Care Assessment Tools were developed to collect and analyse information needed to describe primary care services needed, provided and experienced by the population. Following PCAT, we excluded those individuals who refused to answer any of Q1 - Q4 above. Individuals who responded "not sure, don't remember" to more than 2 questions were also excluded. For those who responded "not sure, don't remember" to only one of the 4 questions, we replaced "not sure, don't remember" with "probably" The mean continuity of care score for an individual was calculated by summing the score of the four questions for each individual and dividing this sum by the number of questions (4 in this case). For a detailed example of the creation of the score, see Jatrana et al (2008a).17 Independent variables We included sociodemographic, health risk behaviour and health status variables as covariates. Independent variables chosen for analyses were based on our review of the literature and our research questions served as a guide in the selection of variables to include in the model of continuity of primary care. Sociodemographic variables in this analysis are age, gender, marital status, ethnicity, family structure, household equivalised income, labour force status, highest level of education achieved, NZDep (area deprivation), and NZiDep (individual deprivation). Health behaviour and health included current smoking status, Kesseler-10 and number of chronic conditions. Categories for the various measures are shown in Table 1. A description of these variables is as follows: Age—Age was calculated at the Wave 3 interview date and categorised into the following age groups: 15-24, 25-44, 45-64, and 65+. Ethnicity—This paper uses the ‘prioritised' concept of ethnicity. With the ‘prioritised' concept, each respondent was assigned to a mutually exclusive ethnic group by means of a prioritisation system commonly used in New Zealand: Māori, if any of the responses to self-identified ethnicity was Māori; Pacific, if any one response was Pacific but not Māori; Asian, if any one response was Asian but not Māori/Pacific; the remainder non-Māori non-Pacific non-Asian (nMnPnA). The nMnPnA category mostly comprises New Zealanders of European descent, but strictly speaking is not an ethnic group. Marital status—Marital status relates to legal marital status and is categorised into currently married, previously married (separated/porced/widowed) and never married. NZDep2001—NZDep2001 is a census-based small-area index of socioeconomic deprivation [24]. The Deprivation index score of dwelling location is derived from NZDep and assigned to the small area of the dwelling. NZDep2001 deprivation scores apply to areas rather than individual people. The index scale used here is from 1 to 5, where 1 = the least deprived 20% of areas and 5 = the most deprived 20% of areas. NZiDep—The NZiDep index is a tool for measuring socioeconomic deprivation for individuals and is based on eight simple questions which take about 2 minutes to administer [25]. The final deprivation score was coded into the following five ordinal categories. Relatively few people have the largest number of deprivation characteristics. 1 = no deprivation characteristics 2 = one deprivation characteristic 3 = two deprivation characteristics 4 = three or four deprivation characteristics 5 = five or more deprivation characteristics Income—In SoFIE, income is collected from every individual over 15 years at every wave. Household income was derived by totalling adult annual personal income (before tax) from all sources received, consumer price index (CPI) adjusted for the quarter ending December 2001 (the first reference quarter of the study), equivalised for household economies of scale using a NZ-specific equivalisation index [26], and categorized into tertiles: low (<$26,109), medium ($26,109 to $43,015) and high (≥$43,016). For the analyses in this paper, equivalised household income at wave 1 was used. Education—The education variable used in this analysis was the highest level of education at Wave 3, categorised as no qualification, school qualification, and post-school qualification. Smoking—A current smoking status variable was created from responses to questions "Do you smoke cigarettes", and "Have you ever been a regular smoker" and is coded into three categories: current smoker, ex-smoker and never smoker. Kessler-10 scale—The Kessler-10 (K-10) is a scale measuring non-specific psychological distress [27, 28]. The K-10 consists of ten questions about non-specific psychological distress and seeks to measure the level of current anxiety and depressive symptoms based on questions about negative emotional states a person may have experienced in the four weeks prior to interview. The scores were grouped into four levels according to the criteria developed by Andrews and Slade (2001): low (10-15), moderate (16-21), high (22-29), and very high (30+) [29, 30]. Chronic diseases—As part of the health module each respondent was asked "have you ever been told by a doctor that you had": Asthma, High Blood Pressure, High Cholesterol, Heart Disease, Diabetes, Stroke, Migraines, Chronic Depression, Manic Depression or Schizophrenia. These data were coded into a co-morbidities index: 0, 1-2, >2 co-morbid diseases. Statistical analysis This paper provides cross-sectional analyses of wave 3 data. The sample used in the analyses consist of 18,320 adult (15 years and above) OSMs. Analyses were carried out using means and 95% confidence intervals (CI) to evaluate the bivariate associations between continuity of care scores and other variables. Ordinary Least Square (OLS) regression was used to adjust for covariates, including age, sex, marital status, ethnicity, household equivalised income, labour force status, small area deprivation, individual deprivation, education, smoking and health (self-assessed health, K-10 and number of chronic conditions). The population used in the regression analyses was 11,915 adult OSMs at wave 3 who had complete information on all the socioeconomic, health behaviour and health characteristics. All counts presented in this paper are random rounded (up or down) to the nearest multiple of 5, with a minimum value of 10, as per the Statistics New Zealand confidentiality protocol. All analyses were performed on unit level data using SAS version 8.2 within the Statistics New Zealand data laboratory. Results Table 1 presents the associations between mean continuity of care scores and demographics, socioeconomic, health and health behaviour characteristics of the respondents. The mean score for continuity of care was 3.10 (95%CI: 3.09-3.11) with a range of 1.0-4.0. As the age of the respondents increased, so did the mean continuity of care score, with older respondents aged 75 and above reporting a mean score of 3.48 (95%CI: 3.45-3.51) as compared to younger respondents aged 15-24 (2.86, 95%CI: 2.83-2.89). There was little variation in the mean score for continuity of care with respect to sex, however, sex CIs do not overlap. Statistically significant variability of continuity of care was also observed for marital status and ethnicity. Income was negatively associated with continuity of care score. For example, those in the lowest income tertile had a mean continuity of care score of 3.23 (95%CI: 3.21-3.25) and those in the highest income tertile had a mean continuity of care score of 3.02 (95%CI: 3.00-3.04). Statistically significant variability of continuity of care was observed for labour force status: those not working had a higher mean continuity of score (3.24, 95%CI: 3.22-3.26) as compared to those who were working (3.02, 95%CI: 3.01-3.03). There was little evidence for significant variation of continuity of care with NZDep, NZiDep, or education. In contrast, significant variability was observed for the smoking covariate. Table 1. Demographic, socioeconomic and health characteristics of study population by mean continuity of care score: SoFIE-Health, 2004-051 Characteristics N Mean (95%CI) All 16630 3.10 (3.09-3.11) Age 15-24 2255 2.86 (2.83-2.89) 25-44 5550 2.95 (2.93-2.97) 45-64 5725 3.17 (3.15-3.19) 65-74 1695 3.38 (3.35-3.41) 75+ 1400 3.48 (3.45-3.51) Sex Male 7365 3.07 (3.05-3.09) Female 9270 3.13 (3.12-3.14) Marital status Currently married 8980 3.16 (3.15-3.17) Previously married 3020 3.24 (3.22-3.26) Never married 4625 2.91 (2.89-2.93) Ethnicity NZ/European 13160 3.11 (3.10-3.12) Māori 1780 3.01 (2.98-3.04) Pacific 695 3.20 (3.15-3.25) Asian 725 3.11 (3.06-3.16)

Summary

Abstract

Aim

Method

Results

Conclusion

Author Information

Acknowledgements

Correspondence

Correspondence Email

Competing Interests

Starfield B. Primary Care: Concept, Evaluation, and Policy. New York: Oxford University Press, 1992.Blumenthal D, Mort E, Edwards J. The efficacy of primary care for vulnerable population groups. Health Services Research 1995;1995(30):253-273.Weiss LJ, Blustein J. Faithful patients: The effect of long-term physician-patient relationships on the costs and use of health care by older Americans. American Journal of Public Health 1996;86(12):1742-1747.Christakis DA, Wright JA, Zimmermann FJ, et al. Continuity of care is associated with high quality care by parental report. Pediatrics 2002;109(4):e54-e59.Becker MH, Drachman RH, Krischt JP. Continuity of pediatrician: new support for an old shibboleth. Journal of Paediatrics and Child Health 1974;84:599-605.Hjortdahl P, Borchgrevink CF. Continuity of care: influence of general practitioners' knowledge about their patients on use of resources in consultations. British Medical Journal 1991;303:1181-1184.Wasson JH, Sauvigne AE, Mogielnicki RP. Continuity of outpatient medical care in elderly men: a randomized trial. JAMA 1984;252:2413-2417.Christakis DA, Wright MD, Koepsell TD, Emerson S, Connell FA. Is greater continuity of care associated with less emergency department utilization? Pediatrics 1999;103(4):738-742.Gill JM, Mainous AG, Nsereko M. The effect of continuity of care on emergency department use. Archives of Family Medicine 2000;9:333-338.Gill JM, Mainous AG. The role of provider continuity in preventing hospitalizations. Archives of Family Medicine 1998;7:352-357.Mainous AG, Gill JM. The importance of continuity of care in the likelihood of future hospitalization: Is site of care equivalent to a primary clinician? American Journal of Public Health 1998;88(10):1539-1541.Gray DJP. The key to personal care. Journal of Royal College of General Practitioner 1979;29:666-678.Sweeney KG, Gray DP. Patients who do not receive continuity of care from their practitioner - are they a vulnerable group? British Journal of General Practice 1995;45:133-135.Bindman AB, Grumbach K, Osmond D, et al. Primary care and receipt of preventive services. Journal of General Internal Medicine 1996;11(5):269-76.Shi L, Starfield B, Xu J. Validating the adult Primary Care Assessment Tool. Journal of Family Practice 2001;50:161-175.Starfield B, Cassady CE, Nanda JP, et al. Consumer experiences and provider perceptions of the quality of primary care: implications for managed care. Journal of Family Practice 1998a(46):3.Jatrana S, Crampton P, Carter K, et al. SoFIE-Health Primary Care: Overview and Early Results: University of Otago, Wellington, 2008a.Carter K, Hayward M, Richardson K. SoFIE-Health Baseline Report: Study Design and Associations of Social Factors and Health in Waves 1 to 3. SoFIE-Health Report 2 University of Otago, Wellington, 2008.Hauck K, Rice N. A longitudinal analysis of mental health mobility in Britain. Health Economics 2004;13:981-1001.Watson N, Wooden M. The HILDA survey four years on. Australian Economic Review 2004;37:343-9.Forrest C, Starfield B. The effect of first-contact care with primary care clinicians on ambulatory health care expenditures Journal of Family Practice 1996;43:40-48.Deutchman ME, Sills D, Connor PD. Perinatal outcomes: a comparison between family physicians and obstetricians. Journal of American Board of Family Practice 1995;8:440-447.Jatrana S, Crampton P. Affiliation with a Primary Care Provider in New Zealand: Who is, Who isnt. Health Policy 2009;91:286-296.Barnett R. \"Wait till it's serious\": health care costs and urban survival strategies of low income groups in Christchurch. New Zealand Medical Journal 2000;113:350-354.Barnett R, Coyle P. Social inequality and general practitioner utilisation: assessing the effects of financial barriers on the use of care by low income groups. New Zealand Medical Journal 1998;111:66-70.Malcolm L. Inequities in access to and utilisation of primary medical care services for M ori and low income New Zealanders. New Zealand Medical Journal 1996;109:356-358.Jatrana S, Crampton P. Primary health care in New Zealand: Who has access? Health Policy 2009b;93(1):1-10.

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Continuity of care (COC) has been defined as seeing the same health care provider over time, and is one of the four main domains of primary care.1 Continuity of care presupposes the existence of a regular source of care over time, regardless of the presence or absence of disease or injury. It is intended to help the provider and the patient build a long-term relationship in order to foster mutual trust between provider and patient, and knowledge of both parties' expectations and needs.2Studies, mainly from the US, have shown that increased continuity of care is associated with positive health outcomes,3 high quality care,4 better medication and appointment compliance, enhanced physician recognition of the patient's health needs, 5and high patient satisfaction with the care.6,7 Research has also suggested that having a regular and consistent source of care is associated with lowering health care costs 3 by decreasing use of emergency services8,9 and hospitalisations,10,11 particularly for ambulatory-care-sensitive conditions (conditions that are more amenable to primary care interventions).The hypothesized benefits of continuity of care with a primary care provider (PCP) are based on the accrued mutual knowledge, trust and communication between patients and providers that arises from repeated contact.1-3 Hence, there is considerable policy interest in defining the characteristics of people who receive continuity of care from their PCPs.While the benefits of continuity of care with a primary care provider are well documented, relatively little is known about those patients who receive continuity of care. Studies which have looked at patients who did not receive continuity of care noted that they were typically younger, female and had relationship problems.12,13 Our goal in this study is to construct a summary measure of continuity of care and to enhance understanding of the prevalence of continuity of care in New Zealand (NZ).While defining the characteristics of those who receive continuity of care is of interest in its own right, it is particularly important in the NZ context, mainly because the different attributes of primary care have not been studied to the same extent as in countries such as the US, leading to a paucity of evidence that grounds the NZ experience in the international context. Moreover, studies from the US mainly focus on a single State, clinic/provider or hospital, or non-elderly population thus restricting the generality of the results.Other studies focus on continuity of care at the level of the whole system, rather than at an individual patient level. This may, in part, be due to the challenge of collecting information at the individual level about aspects of primary care, or the inability of consumers to be valid judges of primary care quality.14This study extends the current literature on continuity of care by using a large national survey and by including a variety of demographic, socioeconomic, health behaviour and health variables. We hypothesise that those who have greater need for care will experience a higher mean continuity of care score.MethodsData This research used SoFIE-Health data, which is part of the Statistics New Zealand-led Survey of Family, Income and Employment (SoFIE). SoFIE is a single fixed panel and is the largest longitudinal survey ever run in New Zealand. It is a nationally representative study of about 22,000 adults, drawn by random sampling of households, interviewed face-to-face. All adults in the original sample are followed for a maximum duration of eight years starting from October 2002, even if their household or family circumstances change. It collects information once a year from the same individuals on income levels, sources and changes; together with the major influences on income such as employment and education experiences, household and family status and changes, demographic factors and health status. The SoFIE-Health module is comprised of 20 minutes of questionnaire time in waves 3 (2004-05), 5 (2006-07) and 7 (2008-09), in the following health-related domains: SF-36 (Short-Form health survey), Kessler-10 (K-10), perceived stress, chronic conditions (heart disease, diabetes, and injury-related disability), tobacco smoking, alcohol consumption, health care utilisation, access and continuity of primary health care, and an individual deprivation score. The health module is administered to the original sample members (OSM). Main outcome variable The main outcome measure used for this work was an index of continuity of care which is assessed by the following four questions in SoFIE-Health. Q1: Would the same doctor or nurse take care of you every time you go? Q2: If you called them, could you talk to the person that knows you best? Q3: Do you think they know you very well as a person? Q4: Do you think they know what medical problems are most important to you? The response categories include definitely, probably, probably not and definitely not and are coded/scored as 4,3,2,1 respectively so that a higher total score indicates higher continuity of care. We based our method on the Primary Care Assessment Tools (PCAT) in order to translate the concept of continuity of care into characteristics that can be measured.15,16 The Primary Care Assessment Tools were developed to collect and analyse information needed to describe primary care services needed, provided and experienced by the population. Following PCAT, we excluded those individuals who refused to answer any of Q1 - Q4 above. Individuals who responded "not sure, don't remember" to more than 2 questions were also excluded. For those who responded "not sure, don't remember" to only one of the 4 questions, we replaced "not sure, don't remember" with "probably" The mean continuity of care score for an individual was calculated by summing the score of the four questions for each individual and dividing this sum by the number of questions (4 in this case). For a detailed example of the creation of the score, see Jatrana et al (2008a).17 Independent variables We included sociodemographic, health risk behaviour and health status variables as covariates. Independent variables chosen for analyses were based on our review of the literature and our research questions served as a guide in the selection of variables to include in the model of continuity of primary care. Sociodemographic variables in this analysis are age, gender, marital status, ethnicity, family structure, household equivalised income, labour force status, highest level of education achieved, NZDep (area deprivation), and NZiDep (individual deprivation). Health behaviour and health included current smoking status, Kesseler-10 and number of chronic conditions. Categories for the various measures are shown in Table 1. A description of these variables is as follows: Age—Age was calculated at the Wave 3 interview date and categorised into the following age groups: 15-24, 25-44, 45-64, and 65+. Ethnicity—This paper uses the ‘prioritised' concept of ethnicity. With the ‘prioritised' concept, each respondent was assigned to a mutually exclusive ethnic group by means of a prioritisation system commonly used in New Zealand: Māori, if any of the responses to self-identified ethnicity was Māori; Pacific, if any one response was Pacific but not Māori; Asian, if any one response was Asian but not Māori/Pacific; the remainder non-Māori non-Pacific non-Asian (nMnPnA). The nMnPnA category mostly comprises New Zealanders of European descent, but strictly speaking is not an ethnic group. Marital status—Marital status relates to legal marital status and is categorised into currently married, previously married (separated/porced/widowed) and never married. NZDep2001—NZDep2001 is a census-based small-area index of socioeconomic deprivation [24]. The Deprivation index score of dwelling location is derived from NZDep and assigned to the small area of the dwelling. NZDep2001 deprivation scores apply to areas rather than individual people. The index scale used here is from 1 to 5, where 1 = the least deprived 20% of areas and 5 = the most deprived 20% of areas. NZiDep—The NZiDep index is a tool for measuring socioeconomic deprivation for individuals and is based on eight simple questions which take about 2 minutes to administer [25]. The final deprivation score was coded into the following five ordinal categories. Relatively few people have the largest number of deprivation characteristics. 1 = no deprivation characteristics 2 = one deprivation characteristic 3 = two deprivation characteristics 4 = three or four deprivation characteristics 5 = five or more deprivation characteristics Income—In SoFIE, income is collected from every individual over 15 years at every wave. Household income was derived by totalling adult annual personal income (before tax) from all sources received, consumer price index (CPI) adjusted for the quarter ending December 2001 (the first reference quarter of the study), equivalised for household economies of scale using a NZ-specific equivalisation index [26], and categorized into tertiles: low (<$26,109), medium ($26,109 to $43,015) and high (≥$43,016). For the analyses in this paper, equivalised household income at wave 1 was used. Education—The education variable used in this analysis was the highest level of education at Wave 3, categorised as no qualification, school qualification, and post-school qualification. Smoking—A current smoking status variable was created from responses to questions "Do you smoke cigarettes", and "Have you ever been a regular smoker" and is coded into three categories: current smoker, ex-smoker and never smoker. Kessler-10 scale—The Kessler-10 (K-10) is a scale measuring non-specific psychological distress [27, 28]. The K-10 consists of ten questions about non-specific psychological distress and seeks to measure the level of current anxiety and depressive symptoms based on questions about negative emotional states a person may have experienced in the four weeks prior to interview. The scores were grouped into four levels according to the criteria developed by Andrews and Slade (2001): low (10-15), moderate (16-21), high (22-29), and very high (30+) [29, 30]. Chronic diseases—As part of the health module each respondent was asked "have you ever been told by a doctor that you had": Asthma, High Blood Pressure, High Cholesterol, Heart Disease, Diabetes, Stroke, Migraines, Chronic Depression, Manic Depression or Schizophrenia. These data were coded into a co-morbidities index: 0, 1-2, >2 co-morbid diseases. Statistical analysis This paper provides cross-sectional analyses of wave 3 data. The sample used in the analyses consist of 18,320 adult (15 years and above) OSMs. Analyses were carried out using means and 95% confidence intervals (CI) to evaluate the bivariate associations between continuity of care scores and other variables. Ordinary Least Square (OLS) regression was used to adjust for covariates, including age, sex, marital status, ethnicity, household equivalised income, labour force status, small area deprivation, individual deprivation, education, smoking and health (self-assessed health, K-10 and number of chronic conditions). The population used in the regression analyses was 11,915 adult OSMs at wave 3 who had complete information on all the socioeconomic, health behaviour and health characteristics. All counts presented in this paper are random rounded (up or down) to the nearest multiple of 5, with a minimum value of 10, as per the Statistics New Zealand confidentiality protocol. All analyses were performed on unit level data using SAS version 8.2 within the Statistics New Zealand data laboratory. Results Table 1 presents the associations between mean continuity of care scores and demographics, socioeconomic, health and health behaviour characteristics of the respondents. The mean score for continuity of care was 3.10 (95%CI: 3.09-3.11) with a range of 1.0-4.0. As the age of the respondents increased, so did the mean continuity of care score, with older respondents aged 75 and above reporting a mean score of 3.48 (95%CI: 3.45-3.51) as compared to younger respondents aged 15-24 (2.86, 95%CI: 2.83-2.89). There was little variation in the mean score for continuity of care with respect to sex, however, sex CIs do not overlap. Statistically significant variability of continuity of care was also observed for marital status and ethnicity. Income was negatively associated with continuity of care score. For example, those in the lowest income tertile had a mean continuity of care score of 3.23 (95%CI: 3.21-3.25) and those in the highest income tertile had a mean continuity of care score of 3.02 (95%CI: 3.00-3.04). Statistically significant variability of continuity of care was observed for labour force status: those not working had a higher mean continuity of score (3.24, 95%CI: 3.22-3.26) as compared to those who were working (3.02, 95%CI: 3.01-3.03). There was little evidence for significant variation of continuity of care with NZDep, NZiDep, or education. In contrast, significant variability was observed for the smoking covariate. Table 1. Demographic, socioeconomic and health characteristics of study population by mean continuity of care score: SoFIE-Health, 2004-051 Characteristics N Mean (95%CI) All 16630 3.10 (3.09-3.11) Age 15-24 2255 2.86 (2.83-2.89) 25-44 5550 2.95 (2.93-2.97) 45-64 5725 3.17 (3.15-3.19) 65-74 1695 3.38 (3.35-3.41) 75+ 1400 3.48 (3.45-3.51) Sex Male 7365 3.07 (3.05-3.09) Female 9270 3.13 (3.12-3.14) Marital status Currently married 8980 3.16 (3.15-3.17) Previously married 3020 3.24 (3.22-3.26) Never married 4625 2.91 (2.89-2.93) Ethnicity NZ/European 13160 3.11 (3.10-3.12) Māori 1780 3.01 (2.98-3.04) Pacific 695 3.20 (3.15-3.25) Asian 725 3.11 (3.06-3.16)

Summary

Abstract

Aim

Method

Results

Conclusion

Author Information

Acknowledgements

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Competing Interests

Starfield B. Primary Care: Concept, Evaluation, and Policy. New York: Oxford University Press, 1992.Blumenthal D, Mort E, Edwards J. The efficacy of primary care for vulnerable population groups. Health Services Research 1995;1995(30):253-273.Weiss LJ, Blustein J. Faithful patients: The effect of long-term physician-patient relationships on the costs and use of health care by older Americans. American Journal of Public Health 1996;86(12):1742-1747.Christakis DA, Wright JA, Zimmermann FJ, et al. Continuity of care is associated with high quality care by parental report. Pediatrics 2002;109(4):e54-e59.Becker MH, Drachman RH, Krischt JP. Continuity of pediatrician: new support for an old shibboleth. Journal of Paediatrics and Child Health 1974;84:599-605.Hjortdahl P, Borchgrevink CF. Continuity of care: influence of general practitioners' knowledge about their patients on use of resources in consultations. British Medical Journal 1991;303:1181-1184.Wasson JH, Sauvigne AE, Mogielnicki RP. Continuity of outpatient medical care in elderly men: a randomized trial. JAMA 1984;252:2413-2417.Christakis DA, Wright MD, Koepsell TD, Emerson S, Connell FA. Is greater continuity of care associated with less emergency department utilization? Pediatrics 1999;103(4):738-742.Gill JM, Mainous AG, Nsereko M. The effect of continuity of care on emergency department use. Archives of Family Medicine 2000;9:333-338.Gill JM, Mainous AG. The role of provider continuity in preventing hospitalizations. Archives of Family Medicine 1998;7:352-357.Mainous AG, Gill JM. The importance of continuity of care in the likelihood of future hospitalization: Is site of care equivalent to a primary clinician? American Journal of Public Health 1998;88(10):1539-1541.Gray DJP. The key to personal care. Journal of Royal College of General Practitioner 1979;29:666-678.Sweeney KG, Gray DP. Patients who do not receive continuity of care from their practitioner - are they a vulnerable group? British Journal of General Practice 1995;45:133-135.Bindman AB, Grumbach K, Osmond D, et al. Primary care and receipt of preventive services. Journal of General Internal Medicine 1996;11(5):269-76.Shi L, Starfield B, Xu J. Validating the adult Primary Care Assessment Tool. Journal of Family Practice 2001;50:161-175.Starfield B, Cassady CE, Nanda JP, et al. Consumer experiences and provider perceptions of the quality of primary care: implications for managed care. Journal of Family Practice 1998a(46):3.Jatrana S, Crampton P, Carter K, et al. SoFIE-Health Primary Care: Overview and Early Results: University of Otago, Wellington, 2008a.Carter K, Hayward M, Richardson K. SoFIE-Health Baseline Report: Study Design and Associations of Social Factors and Health in Waves 1 to 3. SoFIE-Health Report 2 University of Otago, Wellington, 2008.Hauck K, Rice N. A longitudinal analysis of mental health mobility in Britain. Health Economics 2004;13:981-1001.Watson N, Wooden M. The HILDA survey four years on. Australian Economic Review 2004;37:343-9.Forrest C, Starfield B. The effect of first-contact care with primary care clinicians on ambulatory health care expenditures Journal of Family Practice 1996;43:40-48.Deutchman ME, Sills D, Connor PD. Perinatal outcomes: a comparison between family physicians and obstetricians. Journal of American Board of Family Practice 1995;8:440-447.Jatrana S, Crampton P. Affiliation with a Primary Care Provider in New Zealand: Who is, Who isnt. Health Policy 2009;91:286-296.Barnett R. \"Wait till it's serious\": health care costs and urban survival strategies of low income groups in Christchurch. New Zealand Medical Journal 2000;113:350-354.Barnett R, Coyle P. Social inequality and general practitioner utilisation: assessing the effects of financial barriers on the use of care by low income groups. New Zealand Medical Journal 1998;111:66-70.Malcolm L. Inequities in access to and utilisation of primary medical care services for M ori and low income New Zealanders. New Zealand Medical Journal 1996;109:356-358.Jatrana S, Crampton P. Primary health care in New Zealand: Who has access? Health Policy 2009b;93(1):1-10.

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