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Primary care is defined as the entry level into a health system, providing continuous care for the majority of health conditions and also coordinating care delivered by other providers.1,2 Primary care comprises primary medical care as well as activities such as health promotion, prevention and community engagement.3 Strong primary care systems are consistently associated with favourable population health outcomes including lower mortality and higher self-reported health,4–7 as well as reduced health disparities across population groups.8,9 Primary care is therefore central to achieving the two main goals of healthcare—to optimise population health and to minimise disparities—and forms an integral part of the overall health system.1

Delivering cost-effective primary care is essential. Healthcare costs are on the rise internationally, and demand for primary care services has increased on account of the growing chronic disease burden.10 New Zealand is also facing a growing shortage in the general practitioner and nursing workforce, particularly in rural areas.11,12 One potential response to these challenges is to shift delivery of certain primary care services from doctors to nurses.13,14 Evidence suggests that for certain consultations appropriately educated nurses can deliver as high-quality care and achieve equivalent health outcomes for patients compared to doctors.15 The role of the practice nurse has grown and evolved significantly over the last decade in response to policy drivers, government initiatives and legislative changes.16 The positive impacts of primary healthcare nursing on health outcomes as well as the patient experience through nurse clinics, outreach services and new models of care have also been well documented.17

Understanding the frequency with which individuals access primary care services, and the influence of socio-demographic factors on utilisation rates, is essential to inform decision-making regarding service delivery and workforce planning. In New Zealand, reports of general practitioner utilisation range from 2.6 to 6.6 visits per person per year,3,18–20 although methodological variability exists between studies. Fewer studies have investigated nurse utilisation. One study has reported mean nurse utilisation rates of 0.5 visits per person per year,19 while results from the 2015/2016 New Zealand Health Survey show a slightly higher mean of 0.7 visits.21 Furthermore, while consistent patterns have been observed with regard to the influence of age and sex on utilisation rates, conflicting findings have been reported for social deprivation and ethnicity.3,18–20,22,23 Therefore, the aim of this study was to measure utilisation rates for doctors and nurses in primary care general practices across the Comprehensive Care Primary Health Organisation (PHO), and to examine the influence of socio-demographic factors on utilisation rates.

Method

General practices

Data routinely collected for approximately half of all general practices within the Waitemata District Health Board (DHB) area were used in this study. General practices were located in the northern and western regions of Auckland in both urban and rural settings. In New Zealand, enrolment with a PHO is voluntary, although there are incentives for patients to enrol such as lower consultation fees.24 As at April 2017, there were 4.46 million individuals enrolled in a PHO, representing 94% of New Zealand’s population.25

Data collection

De-identified enrolled patient information and consultation data were extracted from general practice computing systems for the period of 1 January 2013 to 31 December 2016. Consultation data were collected using Service Utilisation Reporting (SUR) data. Only invoiced consultations (ie, an invoice has been created in the practice management system, including zero value invoices if these were made) were captured in SUR data. Non-invoiced services, Accident Corporation Claims, immunisations and e-health consultations were therefore not included. Patient and consultation data for all individuals who were enrolled with a Comprehensive Care PHO general practice at any time during the above timeframe, and who had a valid National Health Index (NHI) number, were included.

Patient information

Patient information, including age, sex, ethnicity and social quintile, were collected for all patients for each quarter from January 2013 to December 2016. Ethnicity was self-reported by patients and re-coded to the following ethnic groups used by the Ministry of Health: European, Māori, Pacific Island, Asian or Middle Eastern/Latin American/African.26 Ethnicity was coded using the hierarchical method, in which each individual was assigned one ethnic group using a priority order, with Māori prioritised first, followed by Pacific, Asian, African, Middle Eastern and European/Other, for people reporting multiple ethnicities.27 Social deprivation quintile was recorded using patients’ self-reported residential postcode to provide a deprivation score as per NZDep2013.28 An encrypted NHI number was also obtained for each patient to enable linkage of the patient information and consultation datasets.

Consultation data

For each consultation, the age, sex, ethnicity, social deprivation quintile and encrypted NHI number of the patient seeking care was collected. The date of consultation, type of practitioner consulted and a coded identifier representing the general practice at which the consultation took place was also collected. Practitioner type was coded as ‘Doctor’ (all doctor consultations), ‘Nurse’ (all nurse consultations, including nurse practitioners, registered nurses, enrolled nurses, midwives and nurse specialists) or ‘Other’ (also including nurses, as well as other practitioners such as psychologist, dietician etc, depending on the individual practice). In this study ‘Nurse’ and ‘Other’ consultations have been combined to account for variation in reporting by individual practices. On occasions where multiple practitioners were consulted in a single visit, there was variability between practices regarding how these consultations were recorded. If a patient was billed separately for a doctor and a nurse within the same visit, both a ‘Doctor’ consultation and a ‘Nurse’ consultation were recorded. However, if separate billings were not generated for the doctor and nurse consultations, only the consultation for the doctor was recorded and therefore captured in the SUR data.

Statistical analysis

Data were analysed using the statistical software package SAS version 9.4 (SAS Institute Inc., Cary, NC US). Descriptive statistics for doctor and nurse utilisation rates were calculated. The numerator for calculating utilisation rates was the total number of consultations over the four-year period. The denominator was the exposure variable ‘patient years’ reflecting the total number of patients enrolled across the four-year period. The average was calculated using the number of consultations divided by the total number of patient years, taking into account partial year enrolments. To calculate the percentage of zero consultations, weighting was applied to cases such that the number of consultations per year was weighted by the proportion of the year in which the patient was enrolled (ie, 0.25 for patients enrolled in one quarter, 0.50 for two quarters, 0.75 for three quarters and 1.0 for four quarters). This approach was used as patient enrolments varied between quarters due to new patients enrolling in and existing patients dropping out of general practices. Cases with invalid or missing NHI numbers or practitioner type were excluded from analyses. General practices affiliated with the National Hauora Coalition (NHC), a Māori-led health and social organisation, were coded to enable comparison of utilisation rates with non-NHC affiliated practices. Standardised consultation rates were calculated for general practices controlling for age, sex, ethnicity and social deprivation quintile of patients enrolled at each practice.

Ethics approval

Ethical approval for this study was granted by the Auckland University of Technology Ethics Committee (17/143).

Results

Enrolled patients

A total of 3,861,117 patient records were extracted from 66 general practices across the time period, of which 3,855,445 (99.9%) had valid NHI numbers and were included in analyses. An average of 240,965 patients were enrolled in the PHO across the study period. Characteristics of enrolled patients in the first (January–March 2013) and final (October–December 2016) quarters compared to the national population are shown in Table 1. The age and sex profile of enrolled patients remained largely unchanged across the study period and closely resembled the age and sex profile of the national population. The proportion of European patients declined slightly over the study period, while the proportion of Asian patients increased. Compared to the New Zealand population, there was a higher proportion of Asian patients and a lower proportion of Māori and Pacific Island patients. Enrolled patients on average resided in less socially deprived areas compared to the national population.

Table 1: Demographic characteristics of enrolled patients in Comprehensive Care PHO compared to the New Zealand and Auckland populations.

Abbreviations: MELAA, Middle Eastern/Latin American/African; PHO, primary health organisation.
aEthnicity for Comprehensive Care PHO coded using priority method; Census data recorded each ethnic group identified.
bIncludes unknown, not stated, refused to answer, response unidentifiable.
cDerived from NZDep2013. Equal proportions of the population live in each quintile nationally. NZDep2013 data are reported for the Auckland territorial authority.30

Utilisation rates for doctors

Data for 2,943,885 invoiced doctor consultations were extracted, of which 2,941,624 (99.9%) were for enrolled patients with valid NHI numbers and therefore included in analyses. The overall average utilisation rate for doctors was 3.1 visits per patient year, while 39% of enrolled patients did not consult a doctor in a given year during the study period (Table 2). Females, infants/young children (0–5 years) and older adults (65–74, 75–84 and 85+ years) had the highest doctor utilisation rates. Doctor consultation rates were highest for European patients, patients residing in the most deprived quintile and for NHC-affiliated practices. Doctor utilisation rates remained stable across the study period, although seasonal variation was evident with higher utilisation observed in the July–September quarters. Standardised doctor utilisation rates across individual general practices ranged from 0.7 to 4.9 visits per patient year (Table 3).

Table 2: Annual consultation rates by sex, age, ethnicity, social deprivation, NHC-affiliated practices, year and quarter for 2013–2016.

c


Abbreviations: MELAA, Middle Eastern/Latin American/African; NHC, National Hauora Coalition.
†Average per patient year.
‡Median, 95th percentile and % zero consultations for quarters reported as quarterly rates.

Utilisation rates for nurses

Data for 716,700 invoiced nurse consultations were extracted, of which 716,249 (99.9%) were for enrolled patients with valid NHI numbers. The overall average utilisation rate for nurses was 0.7 visits per patient year (Table 2). Eighty percent of all patients were not captured as consulting with a nurse in any given year. Nurse utilisation rates were highest for older adults aged 75–84 years (Table 2). Māori and Pacific patients had the highest nurse utilisation rates, while European patients had the lowest. Nurse utilisation rates were highest for patients residing in the most socially deprived quintile and for NHC-affiliated practices. There was slight seasonal variation in average consultation rates observed across yearly and quarterly periods. Nurse utilisation rates at individual general practices ranged from 0.001 visits to 3.2 visits per patient year (Table 3).

Table 3: Standardised and unstandardised doctor and nurse utilisation rates across individual general practices.±

c


c

±Standardised by age, sex, ethnicity and social deprivation of patients enrolled at each practice.

Discussion

This study analysed data for 2,941,624 invoiced doctor consultations and 716,249 invoiced nurse consultations across 66 Comprehensive Care general practices over a four-year period. Utilisation rates for doctors and nurses were higher for females, older adults and people residing in more socially deprived areas. These trends are consistent with previous studies.3,18–20,22 Doctor consultations were highest for European patients, also in keeping with the literature.3,19,20,23 The overall average utilisation rate was 3.1 visits per patient year for doctors and 0.7 visits for nurses. These findings for doctor utilisation rates are slightly higher than data from the 2015/2016 New Zealand Health Survey (2.9 visits per person/year),21 and lower than a 2001 Wellington-based study (3.7 visits),19 while nurse utilisation rates are similar to the New Zealand Health Survey (0.7 visits) and slightly higher than the Wellington-based study (0.5 visits).19,21 However, it is important to note the methodological variability between this study and previous studies. Data sources for previous studies include self-report of primary care visits,21–23 a survey of general practitioners,3 consultation data collected from general practice computing systems,18 and billing information databases.20 As such, caution is needed when comparing utilisation rates across studies.

The utilisation rates reported here using SUR data for invoiced consultations do not accurately reflect total utilisation rates in practice. The reasons for this are two-fold: (1) not all consultations undertaken in primary care generate a fee; and (2) there is high variability in reporting practices between clinics. First, consultations not generating a fee include non-billed services and services provided under alternative funding arrangements such as immunisations, Accident Corporation Claims and e-health consultations. Further analysis of consultation data collected by individual practices, including non-billed services, immunisations, Accident Corporation Claims and e-health consultations, is required to more accurately capture primary care utilisation rates for doctors and particularly nurses. Second, regarding reporting practices across different clinics, for patient visits at which more than one practitioner is consulted (eg, doctor and nurse), if separate invoices are not generated for different consultations, only the consultation for the doctor is invoiced and therefore captured in the SUR. There is likely inconsistency between general practices with regard to creating zero value invoices, as suggested by the high variability in utilisation rates between the general practices that is likely not explained by staffing mix alone. As such, actual utilisation rates are likely higher than those reported here, particularly for nurses.

Critically, the SUR data analysed in this report are used for national decision-making and funding assumptions in general practice. PHOs also use SUR data for workforce and facility capacity planning, as well as observing outlier behaviours. However this reliance on SUR data at the national and local levels is problematic given the under-reporting of total consultations. With the rising demand for primary care services and the shrinking general practitioner workforce, there is an emerging opportunity to shift delivery of some services from doctors to nurses through extended scope of practice roles. In order to ensure that appropriate primary care is provided to all New Zealanders, decisions regarding workforce capacity planning for doctors and nurses must be informed by accurate knowledge of service utilisation.

We found that nurse utilisation rates were highest for Māori and Pacific patients, in contrast to a previous study.21 Additionally, doctor and nurse utilisation rates were higher for NHC-affiliated practices compared to non-NHC practices. While the reasons for these trends remain unclear, possible explanations include operational differences such as different models of care between practices, in particular NHC-led practices. For example, some general practices require patients to see a nurse prior to seeing a doctor. The high variability observed in utilisation rates across the 66 general practices in this study highlights an area for improvement with regard to how consultations are recorded, in particular for visits at which more than one practitioner is consulted and for visits not generating a fee. Establishing standardised coding for all consultations and activities would also facilitate more accurate capturing of consultation rates.

A strength of the present study is the large volume of data analysed covering four years of primary care consultations; in comparison previous studies have reported data for a single 12-month period3,18–20,23 or two separate 12-month periods.22 However, there are several important limitations to acknowledge. Further limitations, other than those associated with the use of SUR data as outlined above, include the analysis of data for only those patients who were enrolled in a practice. This is especially relevant for accident and medical clinics which serve a higher proportion of casual, non-enrolled patients. Patient ethnicity was coded using a single priority classification, precluding analysis of patients reporting multiple ethnicities. In the 2013 Census, 11.2% of New Zealanders identified with more than one ethnic group, with more than half of Māori (53.5%) identifying with at least one other ethnic group.31 As such, further analysis of utilisation rates taking into account patients reporting multiple ethnicities is needed, in addition to analysis of all other consultation types.

Summary

Abstract

Aim

To examine socio-demographic trends in doctor and nurse utilisation rates for invoiced consultations across Comprehensive Care Primary Health Organisation (PHO).

Method

De-identified enrolled patient information and Service Utilisation Reporting data for invoiced consultations were extracted from all general practices for January 2013-December 2016. Utilisation rates were calculated using the number of enrolled patients as the denominator.

Results

Data for 3,657,873 invoiced consultations across 66 general practices were analysed, including 2,941,624 doctor and 716,249 nurse consultations. Average utilisation rates were 3.1 visits per patient year for doctors and 0.7 visits for nurses, with considerable variability between practices. Utilisation rates were higher for females (3.3 visits for doctors; 0.8 for nurses), older adults (5.0-6.9; 1.3-1.6 visits) and patients residing in the most socially deprived quintile (3.3; 1.6 visits). European patients had the highest doctor utilisation rates (3.2 visits), while Mori and Pacific patients had the highest nurse utilisation rates (1.1 and 1.3 visits, respectively).

Conclusion

Females, older adults and people residing in socially deprived areas utilise primary care more frequently according to invoiced consultation data. Analysis of all other consultations, including immunisations, Accident Corporation Claims and non-billed services is needed to more accurately capture utilisation rates, particularly for nurses, to better inform national decision-making, workforce planning and funding assumptions.

Author Information

- Jennifer N Baldwin, Postdoctoral Research Fellow, Faculty of Health and Environmental Sciences, Auckland University of Technology, Auckland; Nick Garrett, Biostatistician/Senior Research Fellow, Faculty of Health and Environmental Sciences, Auckland U

Acknowledgements

This project was funded by Comprehensive Care PHO. The authors wish to thank Aimee Legge for her role in extracting data.

Correspondence

Professor Stephen Neville, School of Clinical Sciences, Faculty of Health and Environmental Sciences, AUT University, Private Bag 92006, Auckland 1142.

Correspondence Email

stephen.neville@aut.ac.nz

Competing Interests

Rachael Evans (Director of Nursing), Rosey Buchan (Nurse Leader, Workforce Development) and Craig Murray (General Manager Operations) work with Comprehensive Care PHO. Rachael Evans (formerly Calverley) is currently a member on the AUT Nursing Advisory Committee. The committee's focus is on providing advice on undergraduate and postgraduate nursing programme delivery at AUT.

  1. Starfield B. Primary care: balancing health needs, services, and technology. New York: Oxford University Press 1998.
  2. Starfield B. Is primary care essential? Lancet 1994;344(8930):1129-33.
  3. Crampton P, Jatrana S, Lay-Yee R, et al. Exposure to primary medical care in New Zealand: number and duration of general practitioner visits. N Z Med J 2007; 120(1256).
  4. Macinko J, Starfield B, Shi L. The contribution of primary care systems to health outcomes within Organization for Economic Cooperation and Development (OECD) countries, 1970–1998. Health Serv Res 2003; 38(3):831–65.
  5. Gulliford MC. Availability of primary care doctors and population health in England: is there an association? J Publ Health 2002; 24(4):252–54.
  6. Kringos DS, Boerma W, van der Zee J, et al. Europe’s strong primary care systems are linked to better population health but also to higher health spending. Health Aff 2013; 32(4):686–94.
  7. Starfield B, Shi L, Macinko J. Contribution of primary care to health systems and health. Milbank Q 2005; 83(3):457–502.
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  9. Shi L, Macinko J, Starfield B, et al. Primary care, social inequalities and all-cause, heart disease and cancer mortality in US counties: a comparison between urban and non-urban areas. Public Health 2005; 119(8):699–710.
  10. Fisher ES, Bynum JP, Skinner JS. Slowing the Growth of Health Care Costs—Lessons from Regional Variation. N Engl J Med 2009; 360(9):849–52. doi: 10.1056/NEJMp0809794
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Primary care is defined as the entry level into a health system, providing continuous care for the majority of health conditions and also coordinating care delivered by other providers.1,2 Primary care comprises primary medical care as well as activities such as health promotion, prevention and community engagement.3 Strong primary care systems are consistently associated with favourable population health outcomes including lower mortality and higher self-reported health,4–7 as well as reduced health disparities across population groups.8,9 Primary care is therefore central to achieving the two main goals of healthcare—to optimise population health and to minimise disparities—and forms an integral part of the overall health system.1

Delivering cost-effective primary care is essential. Healthcare costs are on the rise internationally, and demand for primary care services has increased on account of the growing chronic disease burden.10 New Zealand is also facing a growing shortage in the general practitioner and nursing workforce, particularly in rural areas.11,12 One potential response to these challenges is to shift delivery of certain primary care services from doctors to nurses.13,14 Evidence suggests that for certain consultations appropriately educated nurses can deliver as high-quality care and achieve equivalent health outcomes for patients compared to doctors.15 The role of the practice nurse has grown and evolved significantly over the last decade in response to policy drivers, government initiatives and legislative changes.16 The positive impacts of primary healthcare nursing on health outcomes as well as the patient experience through nurse clinics, outreach services and new models of care have also been well documented.17

Understanding the frequency with which individuals access primary care services, and the influence of socio-demographic factors on utilisation rates, is essential to inform decision-making regarding service delivery and workforce planning. In New Zealand, reports of general practitioner utilisation range from 2.6 to 6.6 visits per person per year,3,18–20 although methodological variability exists between studies. Fewer studies have investigated nurse utilisation. One study has reported mean nurse utilisation rates of 0.5 visits per person per year,19 while results from the 2015/2016 New Zealand Health Survey show a slightly higher mean of 0.7 visits.21 Furthermore, while consistent patterns have been observed with regard to the influence of age and sex on utilisation rates, conflicting findings have been reported for social deprivation and ethnicity.3,18–20,22,23 Therefore, the aim of this study was to measure utilisation rates for doctors and nurses in primary care general practices across the Comprehensive Care Primary Health Organisation (PHO), and to examine the influence of socio-demographic factors on utilisation rates.

Method

General practices

Data routinely collected for approximately half of all general practices within the Waitemata District Health Board (DHB) area were used in this study. General practices were located in the northern and western regions of Auckland in both urban and rural settings. In New Zealand, enrolment with a PHO is voluntary, although there are incentives for patients to enrol such as lower consultation fees.24 As at April 2017, there were 4.46 million individuals enrolled in a PHO, representing 94% of New Zealand’s population.25

Data collection

De-identified enrolled patient information and consultation data were extracted from general practice computing systems for the period of 1 January 2013 to 31 December 2016. Consultation data were collected using Service Utilisation Reporting (SUR) data. Only invoiced consultations (ie, an invoice has been created in the practice management system, including zero value invoices if these were made) were captured in SUR data. Non-invoiced services, Accident Corporation Claims, immunisations and e-health consultations were therefore not included. Patient and consultation data for all individuals who were enrolled with a Comprehensive Care PHO general practice at any time during the above timeframe, and who had a valid National Health Index (NHI) number, were included.

Patient information

Patient information, including age, sex, ethnicity and social quintile, were collected for all patients for each quarter from January 2013 to December 2016. Ethnicity was self-reported by patients and re-coded to the following ethnic groups used by the Ministry of Health: European, Māori, Pacific Island, Asian or Middle Eastern/Latin American/African.26 Ethnicity was coded using the hierarchical method, in which each individual was assigned one ethnic group using a priority order, with Māori prioritised first, followed by Pacific, Asian, African, Middle Eastern and European/Other, for people reporting multiple ethnicities.27 Social deprivation quintile was recorded using patients’ self-reported residential postcode to provide a deprivation score as per NZDep2013.28 An encrypted NHI number was also obtained for each patient to enable linkage of the patient information and consultation datasets.

Consultation data

For each consultation, the age, sex, ethnicity, social deprivation quintile and encrypted NHI number of the patient seeking care was collected. The date of consultation, type of practitioner consulted and a coded identifier representing the general practice at which the consultation took place was also collected. Practitioner type was coded as ‘Doctor’ (all doctor consultations), ‘Nurse’ (all nurse consultations, including nurse practitioners, registered nurses, enrolled nurses, midwives and nurse specialists) or ‘Other’ (also including nurses, as well as other practitioners such as psychologist, dietician etc, depending on the individual practice). In this study ‘Nurse’ and ‘Other’ consultations have been combined to account for variation in reporting by individual practices. On occasions where multiple practitioners were consulted in a single visit, there was variability between practices regarding how these consultations were recorded. If a patient was billed separately for a doctor and a nurse within the same visit, both a ‘Doctor’ consultation and a ‘Nurse’ consultation were recorded. However, if separate billings were not generated for the doctor and nurse consultations, only the consultation for the doctor was recorded and therefore captured in the SUR data.

Statistical analysis

Data were analysed using the statistical software package SAS version 9.4 (SAS Institute Inc., Cary, NC US). Descriptive statistics for doctor and nurse utilisation rates were calculated. The numerator for calculating utilisation rates was the total number of consultations over the four-year period. The denominator was the exposure variable ‘patient years’ reflecting the total number of patients enrolled across the four-year period. The average was calculated using the number of consultations divided by the total number of patient years, taking into account partial year enrolments. To calculate the percentage of zero consultations, weighting was applied to cases such that the number of consultations per year was weighted by the proportion of the year in which the patient was enrolled (ie, 0.25 for patients enrolled in one quarter, 0.50 for two quarters, 0.75 for three quarters and 1.0 for four quarters). This approach was used as patient enrolments varied between quarters due to new patients enrolling in and existing patients dropping out of general practices. Cases with invalid or missing NHI numbers or practitioner type were excluded from analyses. General practices affiliated with the National Hauora Coalition (NHC), a Māori-led health and social organisation, were coded to enable comparison of utilisation rates with non-NHC affiliated practices. Standardised consultation rates were calculated for general practices controlling for age, sex, ethnicity and social deprivation quintile of patients enrolled at each practice.

Ethics approval

Ethical approval for this study was granted by the Auckland University of Technology Ethics Committee (17/143).

Results

Enrolled patients

A total of 3,861,117 patient records were extracted from 66 general practices across the time period, of which 3,855,445 (99.9%) had valid NHI numbers and were included in analyses. An average of 240,965 patients were enrolled in the PHO across the study period. Characteristics of enrolled patients in the first (January–March 2013) and final (October–December 2016) quarters compared to the national population are shown in Table 1. The age and sex profile of enrolled patients remained largely unchanged across the study period and closely resembled the age and sex profile of the national population. The proportion of European patients declined slightly over the study period, while the proportion of Asian patients increased. Compared to the New Zealand population, there was a higher proportion of Asian patients and a lower proportion of Māori and Pacific Island patients. Enrolled patients on average resided in less socially deprived areas compared to the national population.

Table 1: Demographic characteristics of enrolled patients in Comprehensive Care PHO compared to the New Zealand and Auckland populations.

Abbreviations: MELAA, Middle Eastern/Latin American/African; PHO, primary health organisation.
aEthnicity for Comprehensive Care PHO coded using priority method; Census data recorded each ethnic group identified.
bIncludes unknown, not stated, refused to answer, response unidentifiable.
cDerived from NZDep2013. Equal proportions of the population live in each quintile nationally. NZDep2013 data are reported for the Auckland territorial authority.30

Utilisation rates for doctors

Data for 2,943,885 invoiced doctor consultations were extracted, of which 2,941,624 (99.9%) were for enrolled patients with valid NHI numbers and therefore included in analyses. The overall average utilisation rate for doctors was 3.1 visits per patient year, while 39% of enrolled patients did not consult a doctor in a given year during the study period (Table 2). Females, infants/young children (0–5 years) and older adults (65–74, 75–84 and 85+ years) had the highest doctor utilisation rates. Doctor consultation rates were highest for European patients, patients residing in the most deprived quintile and for NHC-affiliated practices. Doctor utilisation rates remained stable across the study period, although seasonal variation was evident with higher utilisation observed in the July–September quarters. Standardised doctor utilisation rates across individual general practices ranged from 0.7 to 4.9 visits per patient year (Table 3).

Table 2: Annual consultation rates by sex, age, ethnicity, social deprivation, NHC-affiliated practices, year and quarter for 2013–2016.

c


Abbreviations: MELAA, Middle Eastern/Latin American/African; NHC, National Hauora Coalition.
†Average per patient year.
‡Median, 95th percentile and % zero consultations for quarters reported as quarterly rates.

Utilisation rates for nurses

Data for 716,700 invoiced nurse consultations were extracted, of which 716,249 (99.9%) were for enrolled patients with valid NHI numbers. The overall average utilisation rate for nurses was 0.7 visits per patient year (Table 2). Eighty percent of all patients were not captured as consulting with a nurse in any given year. Nurse utilisation rates were highest for older adults aged 75–84 years (Table 2). Māori and Pacific patients had the highest nurse utilisation rates, while European patients had the lowest. Nurse utilisation rates were highest for patients residing in the most socially deprived quintile and for NHC-affiliated practices. There was slight seasonal variation in average consultation rates observed across yearly and quarterly periods. Nurse utilisation rates at individual general practices ranged from 0.001 visits to 3.2 visits per patient year (Table 3).

Table 3: Standardised and unstandardised doctor and nurse utilisation rates across individual general practices.±

c


c

±Standardised by age, sex, ethnicity and social deprivation of patients enrolled at each practice.

Discussion

This study analysed data for 2,941,624 invoiced doctor consultations and 716,249 invoiced nurse consultations across 66 Comprehensive Care general practices over a four-year period. Utilisation rates for doctors and nurses were higher for females, older adults and people residing in more socially deprived areas. These trends are consistent with previous studies.3,18–20,22 Doctor consultations were highest for European patients, also in keeping with the literature.3,19,20,23 The overall average utilisation rate was 3.1 visits per patient year for doctors and 0.7 visits for nurses. These findings for doctor utilisation rates are slightly higher than data from the 2015/2016 New Zealand Health Survey (2.9 visits per person/year),21 and lower than a 2001 Wellington-based study (3.7 visits),19 while nurse utilisation rates are similar to the New Zealand Health Survey (0.7 visits) and slightly higher than the Wellington-based study (0.5 visits).19,21 However, it is important to note the methodological variability between this study and previous studies. Data sources for previous studies include self-report of primary care visits,21–23 a survey of general practitioners,3 consultation data collected from general practice computing systems,18 and billing information databases.20 As such, caution is needed when comparing utilisation rates across studies.

The utilisation rates reported here using SUR data for invoiced consultations do not accurately reflect total utilisation rates in practice. The reasons for this are two-fold: (1) not all consultations undertaken in primary care generate a fee; and (2) there is high variability in reporting practices between clinics. First, consultations not generating a fee include non-billed services and services provided under alternative funding arrangements such as immunisations, Accident Corporation Claims and e-health consultations. Further analysis of consultation data collected by individual practices, including non-billed services, immunisations, Accident Corporation Claims and e-health consultations, is required to more accurately capture primary care utilisation rates for doctors and particularly nurses. Second, regarding reporting practices across different clinics, for patient visits at which more than one practitioner is consulted (eg, doctor and nurse), if separate invoices are not generated for different consultations, only the consultation for the doctor is invoiced and therefore captured in the SUR. There is likely inconsistency between general practices with regard to creating zero value invoices, as suggested by the high variability in utilisation rates between the general practices that is likely not explained by staffing mix alone. As such, actual utilisation rates are likely higher than those reported here, particularly for nurses.

Critically, the SUR data analysed in this report are used for national decision-making and funding assumptions in general practice. PHOs also use SUR data for workforce and facility capacity planning, as well as observing outlier behaviours. However this reliance on SUR data at the national and local levels is problematic given the under-reporting of total consultations. With the rising demand for primary care services and the shrinking general practitioner workforce, there is an emerging opportunity to shift delivery of some services from doctors to nurses through extended scope of practice roles. In order to ensure that appropriate primary care is provided to all New Zealanders, decisions regarding workforce capacity planning for doctors and nurses must be informed by accurate knowledge of service utilisation.

We found that nurse utilisation rates were highest for Māori and Pacific patients, in contrast to a previous study.21 Additionally, doctor and nurse utilisation rates were higher for NHC-affiliated practices compared to non-NHC practices. While the reasons for these trends remain unclear, possible explanations include operational differences such as different models of care between practices, in particular NHC-led practices. For example, some general practices require patients to see a nurse prior to seeing a doctor. The high variability observed in utilisation rates across the 66 general practices in this study highlights an area for improvement with regard to how consultations are recorded, in particular for visits at which more than one practitioner is consulted and for visits not generating a fee. Establishing standardised coding for all consultations and activities would also facilitate more accurate capturing of consultation rates.

A strength of the present study is the large volume of data analysed covering four years of primary care consultations; in comparison previous studies have reported data for a single 12-month period3,18–20,23 or two separate 12-month periods.22 However, there are several important limitations to acknowledge. Further limitations, other than those associated with the use of SUR data as outlined above, include the analysis of data for only those patients who were enrolled in a practice. This is especially relevant for accident and medical clinics which serve a higher proportion of casual, non-enrolled patients. Patient ethnicity was coded using a single priority classification, precluding analysis of patients reporting multiple ethnicities. In the 2013 Census, 11.2% of New Zealanders identified with more than one ethnic group, with more than half of Māori (53.5%) identifying with at least one other ethnic group.31 As such, further analysis of utilisation rates taking into account patients reporting multiple ethnicities is needed, in addition to analysis of all other consultation types.

Summary

Abstract

Aim

To examine socio-demographic trends in doctor and nurse utilisation rates for invoiced consultations across Comprehensive Care Primary Health Organisation (PHO).

Method

De-identified enrolled patient information and Service Utilisation Reporting data for invoiced consultations were extracted from all general practices for January 2013-December 2016. Utilisation rates were calculated using the number of enrolled patients as the denominator.

Results

Data for 3,657,873 invoiced consultations across 66 general practices were analysed, including 2,941,624 doctor and 716,249 nurse consultations. Average utilisation rates were 3.1 visits per patient year for doctors and 0.7 visits for nurses, with considerable variability between practices. Utilisation rates were higher for females (3.3 visits for doctors; 0.8 for nurses), older adults (5.0-6.9; 1.3-1.6 visits) and patients residing in the most socially deprived quintile (3.3; 1.6 visits). European patients had the highest doctor utilisation rates (3.2 visits), while Mori and Pacific patients had the highest nurse utilisation rates (1.1 and 1.3 visits, respectively).

Conclusion

Females, older adults and people residing in socially deprived areas utilise primary care more frequently according to invoiced consultation data. Analysis of all other consultations, including immunisations, Accident Corporation Claims and non-billed services is needed to more accurately capture utilisation rates, particularly for nurses, to better inform national decision-making, workforce planning and funding assumptions.

Author Information

- Jennifer N Baldwin, Postdoctoral Research Fellow, Faculty of Health and Environmental Sciences, Auckland University of Technology, Auckland; Nick Garrett, Biostatistician/Senior Research Fellow, Faculty of Health and Environmental Sciences, Auckland U

Acknowledgements

This project was funded by Comprehensive Care PHO. The authors wish to thank Aimee Legge for her role in extracting data.

Correspondence

Professor Stephen Neville, School of Clinical Sciences, Faculty of Health and Environmental Sciences, AUT University, Private Bag 92006, Auckland 1142.

Correspondence Email

stephen.neville@aut.ac.nz

Competing Interests

Rachael Evans (Director of Nursing), Rosey Buchan (Nurse Leader, Workforce Development) and Craig Murray (General Manager Operations) work with Comprehensive Care PHO. Rachael Evans (formerly Calverley) is currently a member on the AUT Nursing Advisory Committee. The committee's focus is on providing advice on undergraduate and postgraduate nursing programme delivery at AUT.

  1. Starfield B. Primary care: balancing health needs, services, and technology. New York: Oxford University Press 1998.
  2. Starfield B. Is primary care essential? Lancet 1994;344(8930):1129-33.
  3. Crampton P, Jatrana S, Lay-Yee R, et al. Exposure to primary medical care in New Zealand: number and duration of general practitioner visits. N Z Med J 2007; 120(1256).
  4. Macinko J, Starfield B, Shi L. The contribution of primary care systems to health outcomes within Organization for Economic Cooperation and Development (OECD) countries, 1970–1998. Health Serv Res 2003; 38(3):831–65.
  5. Gulliford MC. Availability of primary care doctors and population health in England: is there an association? J Publ Health 2002; 24(4):252–54.
  6. Kringos DS, Boerma W, van der Zee J, et al. Europe’s strong primary care systems are linked to better population health but also to higher health spending. Health Aff 2013; 32(4):686–94.
  7. Starfield B, Shi L, Macinko J. Contribution of primary care to health systems and health. Milbank Q 2005; 83(3):457–502.
  8. Shi L, Starfield B, Politzer R, et al. Primary care, self-rated health, and reductions in social disparities in health. Health Serv Res 2002; 37(3):529–50.
  9. Shi L, Macinko J, Starfield B, et al. Primary care, social inequalities and all-cause, heart disease and cancer mortality in US counties: a comparison between urban and non-urban areas. Public Health 2005; 119(8):699–710.
  10. Fisher ES, Bynum JP, Skinner JS. Slowing the Growth of Health Care Costs—Lessons from Regional Variation. N Engl J Med 2009; 360(9):849–52. doi: 10.1056/NEJMp0809794
  11. Goodyear-Smith F, Janes R. New Zealand rural primary health care workforce in 2005: more than just a doctor shortage. Aust J Rural Health 2008; 16(1):40–46.
  12. Murton SA, Pullon SR. Assessment of training capacity in New Zealand general practices: a stocktake in the lower North Island and South Island. N Z Med J 2017;130(1462):11–26.
  13. Jenkins-Clarke S, Carr-Hill R, Dixon P. Teams and seams: skill mix in primary care. J Adv Nurs 1998; 28(5):1120–26.
  14. Whitecross L. Collaboration between GPs and nurse practitioners. The overseas experience and lessons for Australia. Aust Fam Physician 1999; 28(4):349–53.
  15. Laurant M, Reeves D, Hermens R, et al. Substitution of doctors by nurses in primary care. Cochrane Database Syst Rev 2005; 2(2)
  16. Halcomb EJ, Davidson PM, Kaur R, et al. The evolution of nursing in Australian general practice: a comparative analysis of workforce surveys ten years on. BMC Fam Pract 2014; 15(1):52.
  17. Halcomb EJ, Peters K, Davies D. A qualitative evaluation of New Zealand consumers perceptions of general practice nurses. BMC Fam Pract 2013; 14(1):26.
  18. Crampton P, Dowell A, Woodward A, et al. Utilisation rates in capitated primary care centres serving low income populations. N Z Med J 2000; 113(1120):436–38.
  19. Health Utilisation Research Alliance. Ethnicity, socioeconomic deprivation and consultation rates in New Zealand general practice. J Health Serv Res Policy 2006; 11(3):141.
  20. Schluter PJ, Bridgford P, Cook L, et al. Improving the evidence-base for access to primary health care in Canterbury: a panel study. Aust N Z J Public Health 2014; 38(2):171–76.
  21. Ministry of Health. Annual update of key results 2015/16: New Zealand Health Survey: New Zealand Government; 2016 [cited 2017 May 29]. Available from: http://www.health.govt.nz/publication/annual-update-key-results-2015-16-new-zealand-health-survey
  22. Cumming J, Stillman S, Liang Y, et al. The determinants of GP visits in New Zealand. Aust N Z J Public Health 2010; 34(5):451–57.
  23. Scott KM, Marwick JC, Crampton PR. Utilization of general practitioner services in New Zealand and its relationship with income, ethnicity and government subsidy. Health Serv Manage Res 2003; 16(1):45–55.
  24. Jatrana S, Crampton P. Primary health care in New Zealand: Who has access? Health Policy 2009; 93(1):1–10.
  25. New Zealand Ministry of Health. Enrolment in a primary health organisation 2017 [cited 2017 May 29]. Available from: http://www.health.govt.nz/our-work/primary-health-care/about-primary-health-organisations/enrolment-primary-health-organisation
  26. Ministry of Health. Ethnicity code tables New Zealand2010 [cited 2019 1 February]. Available from: http://www.health.govt.nz/nz-health-statistics/data-references/code-tables/common-code-tables/ethnicity-code-tables
  27. Statistics New Zealand. Ethnicity New Zealand Standard Classification, V1.0 2005 [cited 2017 May 29]. Available from: http://www.stats.govt.nz/methods/classifications-and-standards/classification-related-stats-standards/ethnicity.aspx
  28. Atkinson J, Salmond C, Crampton P. NZDep2013 index of deprivation. Wellington: Department of Public Health, University of Otago 2014.
  29. Statistics New Zealand. 2013 Census tables 2015 [cited 2017 15 August]. Available from: http://www.stats.govt.nz/tools_and_services/nzdotstat/tables-by-subject/2013-census-tables.aspxhttp://www.ehinz.ac.nz/indicators/population-information/socioeconomic-deprivation-profile/
  30. Environmental Health Indicators New Zealand. Socioeconomic deprivation profile 2017 [cited 2017 15 August]. Available from:
  31. Statistics New Zealand. 2013 Census QuickStats about culture and identity 2014 [cited 2017 20 July]. Available from: http://www.stats.govt.nz/Census/2013-census/profile-and-summary-reports/quickstats-culture-identity/asian.aspx

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Primary care is defined as the entry level into a health system, providing continuous care for the majority of health conditions and also coordinating care delivered by other providers.1,2 Primary care comprises primary medical care as well as activities such as health promotion, prevention and community engagement.3 Strong primary care systems are consistently associated with favourable population health outcomes including lower mortality and higher self-reported health,4–7 as well as reduced health disparities across population groups.8,9 Primary care is therefore central to achieving the two main goals of healthcare—to optimise population health and to minimise disparities—and forms an integral part of the overall health system.1

Delivering cost-effective primary care is essential. Healthcare costs are on the rise internationally, and demand for primary care services has increased on account of the growing chronic disease burden.10 New Zealand is also facing a growing shortage in the general practitioner and nursing workforce, particularly in rural areas.11,12 One potential response to these challenges is to shift delivery of certain primary care services from doctors to nurses.13,14 Evidence suggests that for certain consultations appropriately educated nurses can deliver as high-quality care and achieve equivalent health outcomes for patients compared to doctors.15 The role of the practice nurse has grown and evolved significantly over the last decade in response to policy drivers, government initiatives and legislative changes.16 The positive impacts of primary healthcare nursing on health outcomes as well as the patient experience through nurse clinics, outreach services and new models of care have also been well documented.17

Understanding the frequency with which individuals access primary care services, and the influence of socio-demographic factors on utilisation rates, is essential to inform decision-making regarding service delivery and workforce planning. In New Zealand, reports of general practitioner utilisation range from 2.6 to 6.6 visits per person per year,3,18–20 although methodological variability exists between studies. Fewer studies have investigated nurse utilisation. One study has reported mean nurse utilisation rates of 0.5 visits per person per year,19 while results from the 2015/2016 New Zealand Health Survey show a slightly higher mean of 0.7 visits.21 Furthermore, while consistent patterns have been observed with regard to the influence of age and sex on utilisation rates, conflicting findings have been reported for social deprivation and ethnicity.3,18–20,22,23 Therefore, the aim of this study was to measure utilisation rates for doctors and nurses in primary care general practices across the Comprehensive Care Primary Health Organisation (PHO), and to examine the influence of socio-demographic factors on utilisation rates.

Method

General practices

Data routinely collected for approximately half of all general practices within the Waitemata District Health Board (DHB) area were used in this study. General practices were located in the northern and western regions of Auckland in both urban and rural settings. In New Zealand, enrolment with a PHO is voluntary, although there are incentives for patients to enrol such as lower consultation fees.24 As at April 2017, there were 4.46 million individuals enrolled in a PHO, representing 94% of New Zealand’s population.25

Data collection

De-identified enrolled patient information and consultation data were extracted from general practice computing systems for the period of 1 January 2013 to 31 December 2016. Consultation data were collected using Service Utilisation Reporting (SUR) data. Only invoiced consultations (ie, an invoice has been created in the practice management system, including zero value invoices if these were made) were captured in SUR data. Non-invoiced services, Accident Corporation Claims, immunisations and e-health consultations were therefore not included. Patient and consultation data for all individuals who were enrolled with a Comprehensive Care PHO general practice at any time during the above timeframe, and who had a valid National Health Index (NHI) number, were included.

Patient information

Patient information, including age, sex, ethnicity and social quintile, were collected for all patients for each quarter from January 2013 to December 2016. Ethnicity was self-reported by patients and re-coded to the following ethnic groups used by the Ministry of Health: European, Māori, Pacific Island, Asian or Middle Eastern/Latin American/African.26 Ethnicity was coded using the hierarchical method, in which each individual was assigned one ethnic group using a priority order, with Māori prioritised first, followed by Pacific, Asian, African, Middle Eastern and European/Other, for people reporting multiple ethnicities.27 Social deprivation quintile was recorded using patients’ self-reported residential postcode to provide a deprivation score as per NZDep2013.28 An encrypted NHI number was also obtained for each patient to enable linkage of the patient information and consultation datasets.

Consultation data

For each consultation, the age, sex, ethnicity, social deprivation quintile and encrypted NHI number of the patient seeking care was collected. The date of consultation, type of practitioner consulted and a coded identifier representing the general practice at which the consultation took place was also collected. Practitioner type was coded as ‘Doctor’ (all doctor consultations), ‘Nurse’ (all nurse consultations, including nurse practitioners, registered nurses, enrolled nurses, midwives and nurse specialists) or ‘Other’ (also including nurses, as well as other practitioners such as psychologist, dietician etc, depending on the individual practice). In this study ‘Nurse’ and ‘Other’ consultations have been combined to account for variation in reporting by individual practices. On occasions where multiple practitioners were consulted in a single visit, there was variability between practices regarding how these consultations were recorded. If a patient was billed separately for a doctor and a nurse within the same visit, both a ‘Doctor’ consultation and a ‘Nurse’ consultation were recorded. However, if separate billings were not generated for the doctor and nurse consultations, only the consultation for the doctor was recorded and therefore captured in the SUR data.

Statistical analysis

Data were analysed using the statistical software package SAS version 9.4 (SAS Institute Inc., Cary, NC US). Descriptive statistics for doctor and nurse utilisation rates were calculated. The numerator for calculating utilisation rates was the total number of consultations over the four-year period. The denominator was the exposure variable ‘patient years’ reflecting the total number of patients enrolled across the four-year period. The average was calculated using the number of consultations divided by the total number of patient years, taking into account partial year enrolments. To calculate the percentage of zero consultations, weighting was applied to cases such that the number of consultations per year was weighted by the proportion of the year in which the patient was enrolled (ie, 0.25 for patients enrolled in one quarter, 0.50 for two quarters, 0.75 for three quarters and 1.0 for four quarters). This approach was used as patient enrolments varied between quarters due to new patients enrolling in and existing patients dropping out of general practices. Cases with invalid or missing NHI numbers or practitioner type were excluded from analyses. General practices affiliated with the National Hauora Coalition (NHC), a Māori-led health and social organisation, were coded to enable comparison of utilisation rates with non-NHC affiliated practices. Standardised consultation rates were calculated for general practices controlling for age, sex, ethnicity and social deprivation quintile of patients enrolled at each practice.

Ethics approval

Ethical approval for this study was granted by the Auckland University of Technology Ethics Committee (17/143).

Results

Enrolled patients

A total of 3,861,117 patient records were extracted from 66 general practices across the time period, of which 3,855,445 (99.9%) had valid NHI numbers and were included in analyses. An average of 240,965 patients were enrolled in the PHO across the study period. Characteristics of enrolled patients in the first (January–March 2013) and final (October–December 2016) quarters compared to the national population are shown in Table 1. The age and sex profile of enrolled patients remained largely unchanged across the study period and closely resembled the age and sex profile of the national population. The proportion of European patients declined slightly over the study period, while the proportion of Asian patients increased. Compared to the New Zealand population, there was a higher proportion of Asian patients and a lower proportion of Māori and Pacific Island patients. Enrolled patients on average resided in less socially deprived areas compared to the national population.

Table 1: Demographic characteristics of enrolled patients in Comprehensive Care PHO compared to the New Zealand and Auckland populations.

Abbreviations: MELAA, Middle Eastern/Latin American/African; PHO, primary health organisation.
aEthnicity for Comprehensive Care PHO coded using priority method; Census data recorded each ethnic group identified.
bIncludes unknown, not stated, refused to answer, response unidentifiable.
cDerived from NZDep2013. Equal proportions of the population live in each quintile nationally. NZDep2013 data are reported for the Auckland territorial authority.30

Utilisation rates for doctors

Data for 2,943,885 invoiced doctor consultations were extracted, of which 2,941,624 (99.9%) were for enrolled patients with valid NHI numbers and therefore included in analyses. The overall average utilisation rate for doctors was 3.1 visits per patient year, while 39% of enrolled patients did not consult a doctor in a given year during the study period (Table 2). Females, infants/young children (0–5 years) and older adults (65–74, 75–84 and 85+ years) had the highest doctor utilisation rates. Doctor consultation rates were highest for European patients, patients residing in the most deprived quintile and for NHC-affiliated practices. Doctor utilisation rates remained stable across the study period, although seasonal variation was evident with higher utilisation observed in the July–September quarters. Standardised doctor utilisation rates across individual general practices ranged from 0.7 to 4.9 visits per patient year (Table 3).

Table 2: Annual consultation rates by sex, age, ethnicity, social deprivation, NHC-affiliated practices, year and quarter for 2013–2016.

c


Abbreviations: MELAA, Middle Eastern/Latin American/African; NHC, National Hauora Coalition.
†Average per patient year.
‡Median, 95th percentile and % zero consultations for quarters reported as quarterly rates.

Utilisation rates for nurses

Data for 716,700 invoiced nurse consultations were extracted, of which 716,249 (99.9%) were for enrolled patients with valid NHI numbers. The overall average utilisation rate for nurses was 0.7 visits per patient year (Table 2). Eighty percent of all patients were not captured as consulting with a nurse in any given year. Nurse utilisation rates were highest for older adults aged 75–84 years (Table 2). Māori and Pacific patients had the highest nurse utilisation rates, while European patients had the lowest. Nurse utilisation rates were highest for patients residing in the most socially deprived quintile and for NHC-affiliated practices. There was slight seasonal variation in average consultation rates observed across yearly and quarterly periods. Nurse utilisation rates at individual general practices ranged from 0.001 visits to 3.2 visits per patient year (Table 3).

Table 3: Standardised and unstandardised doctor and nurse utilisation rates across individual general practices.±

c


c

±Standardised by age, sex, ethnicity and social deprivation of patients enrolled at each practice.

Discussion

This study analysed data for 2,941,624 invoiced doctor consultations and 716,249 invoiced nurse consultations across 66 Comprehensive Care general practices over a four-year period. Utilisation rates for doctors and nurses were higher for females, older adults and people residing in more socially deprived areas. These trends are consistent with previous studies.3,18–20,22 Doctor consultations were highest for European patients, also in keeping with the literature.3,19,20,23 The overall average utilisation rate was 3.1 visits per patient year for doctors and 0.7 visits for nurses. These findings for doctor utilisation rates are slightly higher than data from the 2015/2016 New Zealand Health Survey (2.9 visits per person/year),21 and lower than a 2001 Wellington-based study (3.7 visits),19 while nurse utilisation rates are similar to the New Zealand Health Survey (0.7 visits) and slightly higher than the Wellington-based study (0.5 visits).19,21 However, it is important to note the methodological variability between this study and previous studies. Data sources for previous studies include self-report of primary care visits,21–23 a survey of general practitioners,3 consultation data collected from general practice computing systems,18 and billing information databases.20 As such, caution is needed when comparing utilisation rates across studies.

The utilisation rates reported here using SUR data for invoiced consultations do not accurately reflect total utilisation rates in practice. The reasons for this are two-fold: (1) not all consultations undertaken in primary care generate a fee; and (2) there is high variability in reporting practices between clinics. First, consultations not generating a fee include non-billed services and services provided under alternative funding arrangements such as immunisations, Accident Corporation Claims and e-health consultations. Further analysis of consultation data collected by individual practices, including non-billed services, immunisations, Accident Corporation Claims and e-health consultations, is required to more accurately capture primary care utilisation rates for doctors and particularly nurses. Second, regarding reporting practices across different clinics, for patient visits at which more than one practitioner is consulted (eg, doctor and nurse), if separate invoices are not generated for different consultations, only the consultation for the doctor is invoiced and therefore captured in the SUR. There is likely inconsistency between general practices with regard to creating zero value invoices, as suggested by the high variability in utilisation rates between the general practices that is likely not explained by staffing mix alone. As such, actual utilisation rates are likely higher than those reported here, particularly for nurses.

Critically, the SUR data analysed in this report are used for national decision-making and funding assumptions in general practice. PHOs also use SUR data for workforce and facility capacity planning, as well as observing outlier behaviours. However this reliance on SUR data at the national and local levels is problematic given the under-reporting of total consultations. With the rising demand for primary care services and the shrinking general practitioner workforce, there is an emerging opportunity to shift delivery of some services from doctors to nurses through extended scope of practice roles. In order to ensure that appropriate primary care is provided to all New Zealanders, decisions regarding workforce capacity planning for doctors and nurses must be informed by accurate knowledge of service utilisation.

We found that nurse utilisation rates were highest for Māori and Pacific patients, in contrast to a previous study.21 Additionally, doctor and nurse utilisation rates were higher for NHC-affiliated practices compared to non-NHC practices. While the reasons for these trends remain unclear, possible explanations include operational differences such as different models of care between practices, in particular NHC-led practices. For example, some general practices require patients to see a nurse prior to seeing a doctor. The high variability observed in utilisation rates across the 66 general practices in this study highlights an area for improvement with regard to how consultations are recorded, in particular for visits at which more than one practitioner is consulted and for visits not generating a fee. Establishing standardised coding for all consultations and activities would also facilitate more accurate capturing of consultation rates.

A strength of the present study is the large volume of data analysed covering four years of primary care consultations; in comparison previous studies have reported data for a single 12-month period3,18–20,23 or two separate 12-month periods.22 However, there are several important limitations to acknowledge. Further limitations, other than those associated with the use of SUR data as outlined above, include the analysis of data for only those patients who were enrolled in a practice. This is especially relevant for accident and medical clinics which serve a higher proportion of casual, non-enrolled patients. Patient ethnicity was coded using a single priority classification, precluding analysis of patients reporting multiple ethnicities. In the 2013 Census, 11.2% of New Zealanders identified with more than one ethnic group, with more than half of Māori (53.5%) identifying with at least one other ethnic group.31 As such, further analysis of utilisation rates taking into account patients reporting multiple ethnicities is needed, in addition to analysis of all other consultation types.

Summary

Abstract

Aim

To examine socio-demographic trends in doctor and nurse utilisation rates for invoiced consultations across Comprehensive Care Primary Health Organisation (PHO).

Method

De-identified enrolled patient information and Service Utilisation Reporting data for invoiced consultations were extracted from all general practices for January 2013-December 2016. Utilisation rates were calculated using the number of enrolled patients as the denominator.

Results

Data for 3,657,873 invoiced consultations across 66 general practices were analysed, including 2,941,624 doctor and 716,249 nurse consultations. Average utilisation rates were 3.1 visits per patient year for doctors and 0.7 visits for nurses, with considerable variability between practices. Utilisation rates were higher for females (3.3 visits for doctors; 0.8 for nurses), older adults (5.0-6.9; 1.3-1.6 visits) and patients residing in the most socially deprived quintile (3.3; 1.6 visits). European patients had the highest doctor utilisation rates (3.2 visits), while Mori and Pacific patients had the highest nurse utilisation rates (1.1 and 1.3 visits, respectively).

Conclusion

Females, older adults and people residing in socially deprived areas utilise primary care more frequently according to invoiced consultation data. Analysis of all other consultations, including immunisations, Accident Corporation Claims and non-billed services is needed to more accurately capture utilisation rates, particularly for nurses, to better inform national decision-making, workforce planning and funding assumptions.

Author Information

- Jennifer N Baldwin, Postdoctoral Research Fellow, Faculty of Health and Environmental Sciences, Auckland University of Technology, Auckland; Nick Garrett, Biostatistician/Senior Research Fellow, Faculty of Health and Environmental Sciences, Auckland U

Acknowledgements

This project was funded by Comprehensive Care PHO. The authors wish to thank Aimee Legge for her role in extracting data.

Correspondence

Professor Stephen Neville, School of Clinical Sciences, Faculty of Health and Environmental Sciences, AUT University, Private Bag 92006, Auckland 1142.

Correspondence Email

stephen.neville@aut.ac.nz

Competing Interests

Rachael Evans (Director of Nursing), Rosey Buchan (Nurse Leader, Workforce Development) and Craig Murray (General Manager Operations) work with Comprehensive Care PHO. Rachael Evans (formerly Calverley) is currently a member on the AUT Nursing Advisory Committee. The committee's focus is on providing advice on undergraduate and postgraduate nursing programme delivery at AUT.

  1. Starfield B. Primary care: balancing health needs, services, and technology. New York: Oxford University Press 1998.
  2. Starfield B. Is primary care essential? Lancet 1994;344(8930):1129-33.
  3. Crampton P, Jatrana S, Lay-Yee R, et al. Exposure to primary medical care in New Zealand: number and duration of general practitioner visits. N Z Med J 2007; 120(1256).
  4. Macinko J, Starfield B, Shi L. The contribution of primary care systems to health outcomes within Organization for Economic Cooperation and Development (OECD) countries, 1970–1998. Health Serv Res 2003; 38(3):831–65.
  5. Gulliford MC. Availability of primary care doctors and population health in England: is there an association? J Publ Health 2002; 24(4):252–54.
  6. Kringos DS, Boerma W, van der Zee J, et al. Europe’s strong primary care systems are linked to better population health but also to higher health spending. Health Aff 2013; 32(4):686–94.
  7. Starfield B, Shi L, Macinko J. Contribution of primary care to health systems and health. Milbank Q 2005; 83(3):457–502.
  8. Shi L, Starfield B, Politzer R, et al. Primary care, self-rated health, and reductions in social disparities in health. Health Serv Res 2002; 37(3):529–50.
  9. Shi L, Macinko J, Starfield B, et al. Primary care, social inequalities and all-cause, heart disease and cancer mortality in US counties: a comparison between urban and non-urban areas. Public Health 2005; 119(8):699–710.
  10. Fisher ES, Bynum JP, Skinner JS. Slowing the Growth of Health Care Costs—Lessons from Regional Variation. N Engl J Med 2009; 360(9):849–52. doi: 10.1056/NEJMp0809794
  11. Goodyear-Smith F, Janes R. New Zealand rural primary health care workforce in 2005: more than just a doctor shortage. Aust J Rural Health 2008; 16(1):40–46.
  12. Murton SA, Pullon SR. Assessment of training capacity in New Zealand general practices: a stocktake in the lower North Island and South Island. N Z Med J 2017;130(1462):11–26.
  13. Jenkins-Clarke S, Carr-Hill R, Dixon P. Teams and seams: skill mix in primary care. J Adv Nurs 1998; 28(5):1120–26.
  14. Whitecross L. Collaboration between GPs and nurse practitioners. The overseas experience and lessons for Australia. Aust Fam Physician 1999; 28(4):349–53.
  15. Laurant M, Reeves D, Hermens R, et al. Substitution of doctors by nurses in primary care. Cochrane Database Syst Rev 2005; 2(2)
  16. Halcomb EJ, Davidson PM, Kaur R, et al. The evolution of nursing in Australian general practice: a comparative analysis of workforce surveys ten years on. BMC Fam Pract 2014; 15(1):52.
  17. Halcomb EJ, Peters K, Davies D. A qualitative evaluation of New Zealand consumers perceptions of general practice nurses. BMC Fam Pract 2013; 14(1):26.
  18. Crampton P, Dowell A, Woodward A, et al. Utilisation rates in capitated primary care centres serving low income populations. N Z Med J 2000; 113(1120):436–38.
  19. Health Utilisation Research Alliance. Ethnicity, socioeconomic deprivation and consultation rates in New Zealand general practice. J Health Serv Res Policy 2006; 11(3):141.
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