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Development of a health care policy characterisation model based on use of private health insurance

Development of a health care policy characterisation model based on use of private health insurance Objective: The aim of this study was to develop a policy characterisation process based on measuring shifts in use of private health insurance (PHI) immediately following implementation of changes in federal health care policy. Method: Population-based hospital morbidity data from 1980 to 2001 were used to produce trend lines in the annual proportions of public, privately insured and privately uninsured hospital separations in age-stratified subgroups. A policy characterisation model was developed using visual and statistical assessment of the trend lines associated with changes in federal health care policy. Results: Of eight changes in federal health care policy, two (introduction of Medicare and Lifetime Health Cover) were directly associated with major changes in the trend lines; however, minor changes in trends were associated with several of the other federal policies. Three types of policy effects were characterised by our model: direction change, magnitude change and inhibition. Results from our model suggest that a policy of Lifetime Health Cover, with a sanction for late adoption of PHI, was immediately successful in changing the private: public mix. The desired effect of the 30% rebate was immediate only in the oldest age group (70+ years), however, introduction of the lifetime health cover and limitations in the model restricted the ability to determine whether or if the rebate had a delayed effect at younger ages. Conclusion: An outcome-based policy characterisation model is useful in evaluating immediate effects of changes in health care policy. Introduction government to Australia in 1996 marked a resurgence of Private health insurance (PHI) is one of the foundations policy interest in the uptake of PHI [3]. The justification of the Australian health system [1]. Unlike the Unites for the policies introduced was that falling PHI member- States, however, the Australian Government provides uni- ship, observed since the introduction of Medicare in versal access to free public hospital care, with ambulatory 1984, was thought to have increased the demand on the care and pharmaceuticals being available subject to lim- public system [4,5] and, therefore, promoting growth in ited client co-payments via Medicare and the Pharmaceu- the private sector would take the pressure off public hos- tical Benefits Scheme [2]. The return of a Liberal federal pitals and restore balance to the health care system [6]. Page 1 of 9 (page number not for citation purposes) Australia and New Zealand Health Policy 2005, 2:27 http://www.anzhealthpolicy.com/content/2/1/27 Table 1: Federal health care policy changes (cut points) Federal Health Policy "Cut Points" Cut Point Commencement (and duration) Description of Initiative of initiative* 1 Sept 1981 (- Jan 1984) Abolition of free public hospital care 2 Feb 1984 (- Oct 1986) Medicare introduced (Universal bulk billing and free public hospital care restored) Out of hospital rebate set at 85% of scheduled fee Maximum rebate set at $10 Levy set at 1% 3 Nov 1986 (- June 1993) Medicare levy increased to 1.25% Out of hospital rebate @ 85%/$20 GAP set at $150/annum In hospital rebate set at 75% with no maximum Private hospital insurance to cover remaining 25% 4 1993 (- 1995) Medicare Levy increased to 1.4% 5 1995 (- 1997) Medicare Levy increased to 1.5% 0.2% Surcharge introduced to pay for a guns "buy back" following Port Arthur massacre 6 1997 (-1999) Private Health Insurance Incentive Scheme: Surcharge of 1% introduced for high income household without PHI. GAP cover policies allowed (No GAP and known GAP) Simplified billing (use of billing agents) 7 Jan 1999 (- June 2000) Uncapped 30% PHI† rebate for hospital and ancillary benefits with no means test 8 July 2000 (- Present) Lifetime Health Cover: Differential premiums allowed based on age at initial premium. Informed Consent: Patients provided with quotes on costs prior to procedure commencement * Financial year unless otherwise indicated † Private Health Insurance Subsequent policy initiatives concentrated on increasing develop a process capable of characterising policy changes PHI coverage by a mixture of 'carrots' (the private health according to their observable outcomes. The intention insurance incentive scheme in 1997, partially replaced by being to aid in the analysis of the effects of health care pol- a 30% non-means tested rebate on PHI premiums in icies directed towards reducing the pressure on the public 1999) and 'sticks' (a Medicare levy surcharge in 1997 for hospital system. high income earners who did not take out PHI; and Life- time Health Cover in 2000, whereby higher premiums Methods were paid by those who delayed taking out PHI until after The WA Data Linkage System [10] was used to extract all the age of 30 years) [7]. hospital morbidity data from 1 January 1980 to 31 December 2001 for the State of Western Australia (popu- To date, analyses of the effects of policies aimed at sup- lation 1.8 million), comprising encrypted patient identifi- porting PHI in Australia have primarily centred on ers and episode numbers, age, gender, date of admission, changes in the proportion of the population covered by date of separation and payment classification (public, PHI [2,4,7,8]. However, a distinction between uptake of uninsured private, insured private, or "other"). PHI and use of PHI is archetypal of the distinction between outputs and outcomes, where outputs document The proportion of the total number of separations in each the amount, quality or volume of use of a services product relevant payment category in each year was calculated and outcomes reveal the impact the service has on its par- according to gender and age group (0–16 yrs, 17–39 yrs, ticipants (change in behaviour, attitude or condition) [9]. 40–69 yrs, 70+ yrs). The "other" payment categories, Changes in the uptake of PHI are necessary but do not of which included workers compensation, motor vehicle, themselves provide sufficient evidence to evaluate out- defence force personnel and Veteran Affairs patients, were comes of policies aimed at reducing the pressure on the removed from the analysis, leaving only the categories of public system. Rather, the effectiveness of such policies public, private insured and private uninsured. This was would be better judged by changes in PHI use. done because the study was principally concerned with elective shifts between private insurance and public cate- The aim of this study was to use changes in the utilisation gories; not prescribed payment classifications due to man- of payment classifications for in-patient hospitalisation to datory funding arrangements. Page 2 of 9 (page number not for citation purposes) Australia and New Zealand Health Policy 2005, 2:27 http://www.anzhealthpolicy.com/content/2/1/27 Policy Change Identification of inflection point (cut point) No Yes Policy characterised as Policy characterised as No Effect Having an Effect Significance testing of equality of proportions (series points 2 & 3) Significant Difference Non Significant Difference Inhibitory (Type 3) Change in direction of trend Series point 1 Series point 2 Series point 3 Yes No Year Direction changing Magnitude changing (Type 1) (Type 2) Schematic of th inc Figure 2 luded in the a e iden nalysitificati s on of the trend segments Schematic of the identification of the trend segments included in the analysis. Th Figure 1 e policy characterisation process The policy characterisation process. Development of the Policy Characterisation Model (changes in the magnitude or direction of the slope). The annual relative proportion of episodes in each pay- Inflections were classified as either: ment classification (public, private insured and private uninsured) were graphed as segmented trend lines strati- 1. Not observed (no appreciable difference in either the fied by age group and gender. The development of a magnitude of the slope or direction of trend section two model to characterise the policies was undertaken by ana- relative to trend section one). lysing the interaction of the gender and age specific seg- mented trend lines with the major changes in federal 2. Magnitude changing (the slope of trend section two was health care policy, termed 'cut points' (see table 1) for appreciably different in magnitude to that of trend section each payment classification. The process developed is one) shown in figure 1 with each component described below. 3. Direction changing (the direction of trend section two Stage 1: Identification and classification of inflection points in was different to that of trend section one). adjacent trend segments For each policy change trend segments included in the Where inflections were not observed, the policy change analysis were determined in the following manner (refer was deemed to have had no effect on the trend in utilisa- to figure 2): tion and no further analysis was undertaken (refer to fig- ure 1). However, if an inflection was observed the process  Trend segment one was defined as the segmented trend continued to stage two, as detailed below. line connecting the proportion of episodes two years prior with that one year prior to the policy change (series points Stage 2: Determination of a significant difference in the proportion of episodes 1 and 2). Where an inflection point was identified significance test-  Trend segment two was defined as the segmented trend ing of the equality of the proportion of episodes for series line connecting the proportion of episodes one year prior points two and three (the year immediately prior to the with that in the year of implementation of the policy policy change and the year of implementation of the pol- change (series points 2 and 3). icy change, refer to figure 2) was performed using a z test based on the normal approximation to the binomial dis- Trend segments one and two were assessed visually to tribution. This test used the z statistic to test the two sided determine the occurrence and classification of inflections alternative that two proportions were the same. Page 3 of 9 (page number not for citation purposes) Australia and New Zealand Health Policy 2005, 2:27 http://www.anzhealthpolicy.com/content/2/1/27 0–16Years 40 - 69 Years F1 F1 F2 F2 F3 F3 F4 F4 F5 F5 F6 F6 F7 F7 F8 F8 F1 F1 F2 F2 F3 F3 F4 F4 F5 F5 F6 F6 F7 F7 F8 F8 100 100 100% % % 100 100 100 100% % % % 80 80 80% % % 80 80 80 80% % % % 60 60 60% % % 60 60 60 60% % % % 40 40 40% % % 40 40 40 40% % % % 20 20 20% % % 20 20 20 20% % % % 0% 0% 0% 0% 0% 0% 0% 17 - 39 Years 70 + Years 100 100% % 100 100% % 80 80% % 80 80% % 60 60 60% % % 60 60 60% % % 40 40 40% % % 40 40 40% % % 20 20 20% % % 20 20 20% % % 0% 0% 0% 0% 0% 0% M Ma ale le P Pu ub bllic ic M Ma ale le P Prriiv vat ate e IIns nsur ure ed d M Ma alle e P Prriv ivate ate U Un niins nsur ured ed Fem Fema ale le P Pu ub bllic ic F Fe em ma ale le P Prriiv vat ate e IIns nsu urred ed F Fe em ma alle e P Prriv ivat ate e U Un niins nsur ured ed Th Figure 3 e eight federal cut points overlaid on trend line data for gender and age group The eight federal cut points overlaid on trend line data for gender and age group. Stage 3: Outcome of the significance testing Quantification of the rates of change associated with Characterisation of those policies deemed to have had an inflections impact was undertaken depending upon the results of the So as to investigate in more detail changes in utilisation associated with observed inflections a separate analysis significance testing. A non-significant difference between series points 2 and 3 (p value greater than 0.05) resulted was conducted quantifying changes in the rate of change in the policy being deemed as an inhibitory policy (type of the annual proportion of episodes associated with the 3). However, a significant difference between series points introduction of those policies identified in stage 1 as 2 and 3 (p value less than or equal to 0.05) required the showing an observable inflection. This was achieved by classification of the direction of the inflection to be inte- representing each segmented trend segment as a straight grated into the analysis. line having the following mathematical properties y = a+bx (where 'a' is the intercept and 'b' is the slope). This Stage 4: Integration of the classification of the inflection analysis was carried out for trend segments 1 and 2 (see Those policy changes associated with inflections classified figure 2). Differences in the rate of change (slope of the by stage one as direction changing were subsequently trend segment expressed as percentage change per year) termed direction changing policies (type 1). While those for all payment classifications by gender and age group policy changes associated with inflections classified by were calculated stage one as magnitude changing were subsequently termed magnitude changing policies (type 2). Results Figure 3 shows the temporal positions of the eight federal health care policy cut points overlaid on the segmented Page 4 of 9 (page number not for citation purposes) 1 1980 980 19 198 80 0 19 198 85 5 1 1985 985 199 1990 0 1990 1990 19 199 95 5 1995 1995 200 2000 0 20 2000 00 19 1980 80 1980 1980 1980 19 1985 85 19 19 1985 85 85 19 1990 90 1990 1990 1990 19 1995 95 1995 1995 1995 2000 2000 2000 2000 2000 Australia and New Zealand Health Policy 2005, 2:27 http://www.anzhealthpolicy.com/content/2/1/27 Table 2: The rates of change of the proportion of public and private insured episodes pre and post federal cut points 2 (Medicare) and 8 (Lifetime Health Cover). Age Group Gender Payment Rate of change in proportion Change of Difference in Rate Classification (% change in 1 year) Direction (% change in 1 year) Federal cut point 2 1982–83 1983–84 0–16 years M Public 2.14 22.45 NO 20.312 F 2.60 19.73 NO 17.135 M Private Insured -2.99 -20.32 NO 17.333 F -3.35 -17.65 NO 14.296 17–39 years M Public 4.27 22.82 NO 18.549 F 3.10 15.83 NO 12.730 M Private Insured -5.17 -18.88 NO 13.709 F -3.87 -14.46 NO 10.590 40–69 years M Public 1.38 14.87 NO 13.489 F 1.88 10.52 NO 8.647 M Private Insured -1.99 -13.35 NO 11.362 F -2.44 -9.45 NO 7.002 70+ years M Public 0.17 5.96 NO 5.797 F 1.40 2.80 NO 1.401 M Private Insured -0.68 -5.35 NO 4.674 F -1.91 -2.28 NO 0.370 Federal cut point 8 1998–99 1999–00 0–16 years M Public 0.90 -2.49 Yes 3.398 F 0.74 -1.95 Yes 2.691 M Private Insured -1.13 3.09 Yes 4.219 F -1.06 3.08 Yes 4.143 17–39 years M Public 0.35 -1.85 Yes 2.196 F 1.44 -1.03 Yes 2.475 M Private Insured -0.43 2.81 Yes 3.232 F -1.69 1.98 Yes 3.672 40–69 years M Public 2.04 -2.74 Yes 4.787 F 2.12 -1.01 Yes 3.129 M Private Insured -2.17 3.20 Yes 5.362 F -1.97 1.63 Yes 3.608 trend lines of the proportions of annual episodes in each Federal policy initiatives that were associated with major payment classification in each age group in males and rate changes or inflections in the trend lines were federal females. cut points 2 (the re-introduction of free public hospital care via Medicare) and 8 (Lifetime Health Care). Federal Observation and quantification in changes in trend cut point 2 was associated with acceleration in the rate of In general the shape of the trends was similar in males and decline in the proportion of privately insured episodes females. In some age groups, particularly the 17–39 years and a greater rate of increase in the proportion of public age group, there was a near-constant difference in propor- episodes in all four age groups. tion between the genders. Given this finding to simplify the analysis the genders were combined. The shape of the Federal cut point 8 was another major inflection point segmented trend lines; however, varied significantly associated with a surge in the private insurance payment across age groups, with the two younger age groups expe- classification in all except the oldest age group. For the riencing the largest changes in payment classification younger three age groups the shift in direction was of sim- mainly over the early part of the observation period. The ilar magnitude as shown in table 2. The magnitude of the oldest age group had the least annual differences and a change in rates associated with the introduction of Life- more stable overall trend. time Health Cover was smaller in absolute terms, as well Page 5 of 9 (page number not for citation purposes) Australia and New Zealand Health Policy 2005, 2:27 http://www.anzhealthpolicy.com/content/2/1/27 Table 3: Federal cut points associated with significant (p < 0.05) changes in the proportion of episodes and inflections or substantial changes in trend by age group Federal Healthcare Policy Cut Points Age Group Public Private Insured Private Uninsured Age 0–16 yrs 2,5,6,8 2,5,8 2 Age 17–39 yrs 2,3,5,7,8 2,3,7,8 8 Age 40 – 69 yrs 2,4,5,7,8 2,4,5,7,8 2,8 Age 70+ yrs 2,6 2,6 Shaded areas = no cut points associated with significant changes and inflections or trend changes for the age group/couplet type combination as in the opposite direction to that associated with the Characterisation of policy effects introduction of Medicare. Four types of policies were identified by the policy charac- terisation model. Those that had no effect; type 1, those Less marked changes in the trends, in addition to the that affected the direction of the trend; type 2, those that major ones described above, were observed to coincide affected the magnitude of the trend, but not its direction; with all federal cut points to some degree, although none and type 3, those that inhibited the trend (the pre policy was seen consistently in all combinations of payment trend was positive or negative, but significance testing classification and age group. The largest of these minor indicated no-significant difference in the proportions post rate changes was associated with federal cut point 3 (see policy). It should be noted that type 3 policies prevented table 1) in the youngest age group. These changes (or subdued) a pre-existing trend from continuing. The involved inflections in the segmented trend lines with results of the characterisation of federal policies from absolute differences slightly in excess of 3.5 percent per 1980 to 2001 related to age group are detailed in table 5. year. The remaining observable changes ranged from 2.3 percent to 0.7 percent per year. Discussion In free markets consumers and suppliers are left alone to Significance testing in those cut points deemed to be interact and balance supply and demand for services. It is associated with inflections generally accepted that governments need to intervene in Significance tests of the equivalence of the proportion of health markets to provide certain services and regulate the episodes one year prior to and in the year of implementa- market. This intervention occurs via specific policy action tion for federal policy cut points associated with observa- [11]. In Australia the Commonwealth Government's deci- ble inflections are summarized in tables 3 and 4. Most sion to subsidise PHI has meant that it has increased its federal policy initiatives that showed an observable stake in the private sector alongside its existing stake in the change in trend were also associated with a significant public sector. change (p < 0.05) in private: public mix. The most notable exception to this occurred in the elderly age group. In Controversy has raged about the success of the Common- those aged 70+ years, cut points 7 (designed to increase wealth Government's policies with regard to supporting the proportion of persons holding private health insur- PHI in order to reduce the pressure on the public sector. ance by making it more affordable) was not associated The major debate has centered around the effectiveness of with a significant difference. the 30% rebate and more recently the effectiveness of the Lifetime Health Care policy [4,7,8,2-15]. However, in The privately uninsured payment classification was the most cases, commentators have used evidence relating to least affected by policy changes over time. However, the the changing prevalence of PHI membership, pre and post two most influential policies, being the introduction of policy implementation. This may not be an accurate Medicare (cut point 2) and Lifetime Health Cover (cut method to assess the effectiveness of such policies, point 8), were both associated with significant reductions because the policies themselves may promote the uptake in the proportions of private uninsured patients in several of PHI for non-health related reasons, such as to avoid a age groups, albeit that the shifts were towards the public tax penalty in high income households (cut point 6). This and private insured payment classifications respectively. coupled with the finding that since 1998 the proportion Once again in the oldest age group neither of these cut of PHI fund members with high front-end deductibles has points was associated with a significant difference. significantly increased [4] means that uptake of PHI may Page 6 of 9 (page number not for citation purposes) Australia and New Zealand Health Policy 2005, 2:27 http://www.anzhealthpolicy.com/content/2/1/27 Table 4: Federal cut points associated non-significant (p > 0.05) changes in the proportion of episodes and inflections or substantial changes in trend by age group Federal Healthcare Policy Cut Points Age Group Public Private Insured Private Uninsured Age 0–16 yrs 33,68 Age 17–39 yrs 2,5 Age 40 – 69 yrs Age 70+ yrs 77 2 Shaded areas = no cut points associated with non-significant changes and inflections or trend changes for the age group/couplet type combination not necessarily lead to the expected changes in use of the oldest age group, with no effect observed in the youngest public and private systems. This is quite apart from the age group. Thus the 30% rebate appears to have had the debate about the price elasticity of demand for PHI and desired effect on PHI use (ie reducing the pressure on the the assumption that demand for hospital care is a fixed public system) in the oldest age group, but no immediate commodity [4]. Our study has developed and used a pol- desired effect in the younger age groups. To some extent icy characterisation model based on measuring shifts in this can be explained because younger members are not as the actual use of PHI at the time of receiving hospital serv- likely to be hospitalised compared with older members, ices. This may be a more appropriate methodology for thus reducing the likelihood of an immediate effect on evaluating likely changes in the pressure on the public sys- use. While older Australians are not only more likely to be tem affected by particular policies. hospitalised and therefore have more opportunity to use PHI, but are also more likely to be attracted to purchase The results of our analysis indicate that federal cut point PHI due to reduced cost because the price elasticity of PHI 2, the re-introduction of free public hospital care via is different for younger and older individuals. Medicare, was a magnitude changing policy. This was an unexpected finding since it has been previously assumed Limitations of the model that the introduction of Medicare, following on from an For practical reasons the immediate effects of the policies era when free public hospital care was abolished, would were the only effects able to be characterised by our model be a direction changing policy. However, our data indicate due to the plethora of federal health care policy changes, that a reversal in trend in favour of the public system especially from 1993 onwards. To try to characterise the occurred one year prior to the introduction of Medicare. changes in trends over an extended period would have Federal cut point 8, Lifetime Health Cover, was classified resulted in evaluation of the mix of effects produced by by our model as a direction changing policy in the more than one policy. This is especially relevant when younger three age groups with no effect observed in the examining the effects of the 30% rebate and Lifetime oldest age group (individuals born prior to 1 July 1934 are Health Cover, where only one year separated the two pol- exempt from Lifetime Health Cover). This finding was icy changes. thus consistent with the objective of the policy, which was to reverse the declining trend in possession and use of PHI A second limitation of this policy characterisation method to reduce the burden on the public system. It would is that it cannot accurately take into account enforced appear that this was achieved immediately post-imple- waiting periods, which are mandatorily applied to indi- mentation. viduals taking out PHI who have a previous history of an illness or condition. Thus some underestimation of the The effects of the 30% rebate (federal cut point 7) on lev- effects of policies may be inherent in the model. Extend- els of PHI have been one of the most hotly contested ing the model over two years post policy initiation is political issues surrounding heath care policy in recent problematic, as discussed above, because the effect times. Commentators have argued for and against this observed would then be confounded by subsequent pol- policy initiative mainly on a cost-benefit platform [4, 12, icy changes. Another issue to be taken into account is the 14, 16]. Our analysis found that the effect of federal cut timing and extent of marketing of the policy to the public point 7 was related to age. This policy was associated by government and the private insurance industry. In the immediately in time with a change in the magnitude of case of Lifetime Health Cover, exhaustive marketing, the the existing negative trend (PHI) or a negative to positive 'Run for Cover Campaign', was undertaken over several change of direction (public) in the middle two age groups, months leading up to its implementation. It is reasonable and an inhibitory effect on the downward trend in the to assume that changes in behaviour, in this case purchas- Page 7 of 9 (page number not for citation purposes) Australia and New Zealand Health Policy 2005, 2:27 http://www.anzhealthpolicy.com/content/2/1/27 Table 5: Classification of federal policy effects on trends in age group related annual proportion of episodes by payment classification Federal Age Group cut point 0 – 16 Years 17 – 39 Years 40 – 69 Years 70+ Years Public Private Private Public Private Private Public Private Private Public Private Private Insured Uninsured Insured Uninsured Insured Uninsured Insured Uninsured F1 No trend data available prior to 1980* F2 Type 2 Type 2 Type 2 Type 2 Type 2 Type 3 Type 2 Type 2 Type 2 Type 2 Type 2 Type 3 F3 Type 3 Type 3 Type 2 Type 2 F4 Type 1 Type 1 F5 Type 2 Type 2 Type 1 Type 3 Type 2 Type 2 F6 Type 1 Type 3 Type 1 Type 1 F7 Type 1 Type 2 Type 1 Type 2 Type 3 Type 3 F8 Type 1 Type 1 Type 3 Type 1 Type 1 Type 1 Type 1 Type 1 Type 1 * Since no data was available about the trend 1979–1980 the classification of this policy was not possible. However, in the known historical setting sudden removal of free public hospital care it would be most likely that this policy was a type 1 (direction changing). Type 1: Direction changing, Type 2: Magnitude changing, Type 3: Inhibitory Shaded areas indicate no observable effect from the policy change. ing of PHI, were likely to have been made prior to the pol- with an immediate increase in patients in hospital using icy implementation date, thus some of the waiting period, PHI. While the 30% rebate for PHI introduced 18 months if applicable, would have been served prior to the policy earlier did not have an immediate desired effect, the limi- implementation date. Conversely, advantage could be tations of the model are such that we cannot be certain taken of the 30% rebate at any time after, but not before what, if any, latent contribution to the change in private: January 1999. The net result of these two limitations on public mix may have occurred. From this study we con- our policy characterisation model may be that of cancel- clude that an outcome-based policy characterisation ling each other out in the case of Lifetime Health Cover model is useful in evaluating immediate effects of changes and causing a latent period between cause and effect in in health care policy. the case of the 30% rebate. Competing interests In addition, it could be argued that since the waiting Professor D'Arcy Holman is an independent director of period only applies to pre-existing conditions, those wish- HBF Health Funds inc which is the largest provider of pri- ing to use newly acquired PHI for such a condition would vate health insurance in Western Australia. be doing so to facilitate a more expedient health interven- tion than could be achieved in the public sector. As such Authors' contributions these episodes of care would not normally have been The manuscript has been read and approved by all authors and the requirements for authorship have been observed in the public system over the same period, but rather at a later time. Under these circumstances the wait- met as outlined below. REM was responsible for the con- ing time for benefits may serve to enhance the validity of ception and design of the study; analysis and interpreta- a characterisation model employing a latent period. tion of the data; and drafting and revising the paper. CDJH was responsible for conception and design of the Finally, our policy characterisation model does not allow study; interpretation of the data; and revising the paper. for the possibility of an earlier policy initiative synergising with a subsequent initiative. Thus it is possible that the Acknowledgements The initial construction of the Data Linkage System was funded by the immediate effect of Lifetime Health Cover may have been Western Australian Lotteries Commission. This study was undertaken as a less potent in the absence of the pre-existing 30% rebate. part of a Collaborative Research and Development Venture funded by HBF Health Funds Inc and the WA Department of Health. We would also like Conclusion to thank the WA Department of Health for on-going support of the Data Our study has developed and applied a policy characteri- Linkage Unit. sation model based on measuring shifts in use of PHI immediately prior to, and immediately following imple- References mentation of changes in federal health care policy. Our 1. Sullivan N, Redpath R, O'Donnell A: Public Hospitals: Who's looking after you? The Difficulties in Encouraging Patients to use their Private results indicate that Lifetime Health Cover was associated Page 8 of 9 (page number not for citation purposes) Australia and New Zealand Health Policy 2005, 2:27 http://www.anzhealthpolicy.com/content/2/1/27 Health Insurance in Public Hospitals. Australian Health Review 2002, 25:6-14. 2. Willcox S: Promoting Private Health Insurance in Australia. Health Affairs 2001, 20:152-161. 3. Duckett SJ: The Australian Health Care System. Oxford, Oxford University Press; 2000. 4. Deeble J: The Private Health Insurance Rebate: Report to State and Territory Health Ministers. , National Centre for Epi- demiology and Population Health The Australian National University; 5. McAuley IA: Stress on public hospitals - why private insurance has made it worse. University of Canberra, Discussion paper: Aus- tralian Consumers' Association and the Australian Healthcare Asso- ciation; 2004. 6. Duckett SJ, Jackson TJ: The New health Insurance Rebate: An Inefficient Way of Assisting Public Hospitals. Medical Journal of Australia 2000, 172:439-442. 7. Butler J: Policy Change and Private Health Insurance: Did the Cheapest Policy do the Trick? Australian Health Review 2002, 25:33-41. 8. Cormack M: Private Health Insurance: The Problem Child Faces Adulthood. Australian Health Review 2002, 25:38-51. 9. National Network of Libraries of Medicine: Define Measurable Goals, Outputs and Outcomes. [http://nnlm.gov/libinfo/commu nity/goals.php]. 10. Holman CDJ, Bass AJ, Rouse IL, Hobbs MST: Western Australia: Development of a Health Services Research Linked Data- base. Aust NZ J Public Health 1999, 23:453-459. 11. Whiteford H: Can Research Influence Mental Health Policy? Australian and New Zealand Journal of Psychiatry 2001, 35:458-434. 12. Australian Health Insurance Association: AHIA Submission on PHI Reforms to Senate Legislation Committee: Health Leg- islation Amendment (Private Health Insurance Reform) Bill 2003. Volume 2004. , AHIA; 2003. 13. Harper I: Preserving ChoiceA defence of public support for private health care funding in Australia. Medibank Private 2003. 14. Econtech Pty Ltd, Harper Associates, Hagan P: Easing the Pres- sure: The Intergenerational Report and Private Health Insurance. , Medibank Private; 2004. 15. Access Economics: Striking a Balance: Choice, Access and Affordability in Australian Health Care. , APHA; 2002. 16. Segal L: Why it is time to review the role of private health insurance in Australia. Australian Health Review 2004, 27:3-14. Publish with Bio Med Central and every scientist can read your work free of charge "BioMed Central will be the most significant development for disseminating the results of biomedical researc h in our lifetime." Sir Paul Nurse, Cancer Research UK Your research papers will be: available free of charge to the entire biomedical community peer reviewed and published immediately upon acceptance cited in PubMed and archived on PubMed Central yours — you keep the copyright BioMedcentral Submit your manuscript here: http://www.biomedcentral.com/info/publishing_adv.asp Page 9 of 9 (page number not for citation purposes) http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Australia and New Zealand Health Policy Springer Journals

Development of a health care policy characterisation model based on use of private health insurance

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Springer Journals
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Copyright © 2005 by Moorin and Holman; licensee BioMed Central Ltd.
Subject
Medicine & Public Health; Public Health; Social Policy
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1743-8462
DOI
10.1186/1743-8462-2-27
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16274489
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Abstract

Objective: The aim of this study was to develop a policy characterisation process based on measuring shifts in use of private health insurance (PHI) immediately following implementation of changes in federal health care policy. Method: Population-based hospital morbidity data from 1980 to 2001 were used to produce trend lines in the annual proportions of public, privately insured and privately uninsured hospital separations in age-stratified subgroups. A policy characterisation model was developed using visual and statistical assessment of the trend lines associated with changes in federal health care policy. Results: Of eight changes in federal health care policy, two (introduction of Medicare and Lifetime Health Cover) were directly associated with major changes in the trend lines; however, minor changes in trends were associated with several of the other federal policies. Three types of policy effects were characterised by our model: direction change, magnitude change and inhibition. Results from our model suggest that a policy of Lifetime Health Cover, with a sanction for late adoption of PHI, was immediately successful in changing the private: public mix. The desired effect of the 30% rebate was immediate only in the oldest age group (70+ years), however, introduction of the lifetime health cover and limitations in the model restricted the ability to determine whether or if the rebate had a delayed effect at younger ages. Conclusion: An outcome-based policy characterisation model is useful in evaluating immediate effects of changes in health care policy. Introduction government to Australia in 1996 marked a resurgence of Private health insurance (PHI) is one of the foundations policy interest in the uptake of PHI [3]. The justification of the Australian health system [1]. Unlike the Unites for the policies introduced was that falling PHI member- States, however, the Australian Government provides uni- ship, observed since the introduction of Medicare in versal access to free public hospital care, with ambulatory 1984, was thought to have increased the demand on the care and pharmaceuticals being available subject to lim- public system [4,5] and, therefore, promoting growth in ited client co-payments via Medicare and the Pharmaceu- the private sector would take the pressure off public hos- tical Benefits Scheme [2]. The return of a Liberal federal pitals and restore balance to the health care system [6]. Page 1 of 9 (page number not for citation purposes) Australia and New Zealand Health Policy 2005, 2:27 http://www.anzhealthpolicy.com/content/2/1/27 Table 1: Federal health care policy changes (cut points) Federal Health Policy "Cut Points" Cut Point Commencement (and duration) Description of Initiative of initiative* 1 Sept 1981 (- Jan 1984) Abolition of free public hospital care 2 Feb 1984 (- Oct 1986) Medicare introduced (Universal bulk billing and free public hospital care restored) Out of hospital rebate set at 85% of scheduled fee Maximum rebate set at $10 Levy set at 1% 3 Nov 1986 (- June 1993) Medicare levy increased to 1.25% Out of hospital rebate @ 85%/$20 GAP set at $150/annum In hospital rebate set at 75% with no maximum Private hospital insurance to cover remaining 25% 4 1993 (- 1995) Medicare Levy increased to 1.4% 5 1995 (- 1997) Medicare Levy increased to 1.5% 0.2% Surcharge introduced to pay for a guns "buy back" following Port Arthur massacre 6 1997 (-1999) Private Health Insurance Incentive Scheme: Surcharge of 1% introduced for high income household without PHI. GAP cover policies allowed (No GAP and known GAP) Simplified billing (use of billing agents) 7 Jan 1999 (- June 2000) Uncapped 30% PHI† rebate for hospital and ancillary benefits with no means test 8 July 2000 (- Present) Lifetime Health Cover: Differential premiums allowed based on age at initial premium. Informed Consent: Patients provided with quotes on costs prior to procedure commencement * Financial year unless otherwise indicated † Private Health Insurance Subsequent policy initiatives concentrated on increasing develop a process capable of characterising policy changes PHI coverage by a mixture of 'carrots' (the private health according to their observable outcomes. The intention insurance incentive scheme in 1997, partially replaced by being to aid in the analysis of the effects of health care pol- a 30% non-means tested rebate on PHI premiums in icies directed towards reducing the pressure on the public 1999) and 'sticks' (a Medicare levy surcharge in 1997 for hospital system. high income earners who did not take out PHI; and Life- time Health Cover in 2000, whereby higher premiums Methods were paid by those who delayed taking out PHI until after The WA Data Linkage System [10] was used to extract all the age of 30 years) [7]. hospital morbidity data from 1 January 1980 to 31 December 2001 for the State of Western Australia (popu- To date, analyses of the effects of policies aimed at sup- lation 1.8 million), comprising encrypted patient identifi- porting PHI in Australia have primarily centred on ers and episode numbers, age, gender, date of admission, changes in the proportion of the population covered by date of separation and payment classification (public, PHI [2,4,7,8]. However, a distinction between uptake of uninsured private, insured private, or "other"). PHI and use of PHI is archetypal of the distinction between outputs and outcomes, where outputs document The proportion of the total number of separations in each the amount, quality or volume of use of a services product relevant payment category in each year was calculated and outcomes reveal the impact the service has on its par- according to gender and age group (0–16 yrs, 17–39 yrs, ticipants (change in behaviour, attitude or condition) [9]. 40–69 yrs, 70+ yrs). The "other" payment categories, Changes in the uptake of PHI are necessary but do not of which included workers compensation, motor vehicle, themselves provide sufficient evidence to evaluate out- defence force personnel and Veteran Affairs patients, were comes of policies aimed at reducing the pressure on the removed from the analysis, leaving only the categories of public system. Rather, the effectiveness of such policies public, private insured and private uninsured. This was would be better judged by changes in PHI use. done because the study was principally concerned with elective shifts between private insurance and public cate- The aim of this study was to use changes in the utilisation gories; not prescribed payment classifications due to man- of payment classifications for in-patient hospitalisation to datory funding arrangements. Page 2 of 9 (page number not for citation purposes) Australia and New Zealand Health Policy 2005, 2:27 http://www.anzhealthpolicy.com/content/2/1/27 Policy Change Identification of inflection point (cut point) No Yes Policy characterised as Policy characterised as No Effect Having an Effect Significance testing of equality of proportions (series points 2 & 3) Significant Difference Non Significant Difference Inhibitory (Type 3) Change in direction of trend Series point 1 Series point 2 Series point 3 Yes No Year Direction changing Magnitude changing (Type 1) (Type 2) Schematic of th inc Figure 2 luded in the a e iden nalysitificati s on of the trend segments Schematic of the identification of the trend segments included in the analysis. Th Figure 1 e policy characterisation process The policy characterisation process. Development of the Policy Characterisation Model (changes in the magnitude or direction of the slope). The annual relative proportion of episodes in each pay- Inflections were classified as either: ment classification (public, private insured and private uninsured) were graphed as segmented trend lines strati- 1. Not observed (no appreciable difference in either the fied by age group and gender. The development of a magnitude of the slope or direction of trend section two model to characterise the policies was undertaken by ana- relative to trend section one). lysing the interaction of the gender and age specific seg- mented trend lines with the major changes in federal 2. Magnitude changing (the slope of trend section two was health care policy, termed 'cut points' (see table 1) for appreciably different in magnitude to that of trend section each payment classification. The process developed is one) shown in figure 1 with each component described below. 3. Direction changing (the direction of trend section two Stage 1: Identification and classification of inflection points in was different to that of trend section one). adjacent trend segments For each policy change trend segments included in the Where inflections were not observed, the policy change analysis were determined in the following manner (refer was deemed to have had no effect on the trend in utilisa- to figure 2): tion and no further analysis was undertaken (refer to fig- ure 1). However, if an inflection was observed the process  Trend segment one was defined as the segmented trend continued to stage two, as detailed below. line connecting the proportion of episodes two years prior with that one year prior to the policy change (series points Stage 2: Determination of a significant difference in the proportion of episodes 1 and 2). Where an inflection point was identified significance test-  Trend segment two was defined as the segmented trend ing of the equality of the proportion of episodes for series line connecting the proportion of episodes one year prior points two and three (the year immediately prior to the with that in the year of implementation of the policy policy change and the year of implementation of the pol- change (series points 2 and 3). icy change, refer to figure 2) was performed using a z test based on the normal approximation to the binomial dis- Trend segments one and two were assessed visually to tribution. This test used the z statistic to test the two sided determine the occurrence and classification of inflections alternative that two proportions were the same. Page 3 of 9 (page number not for citation purposes) Australia and New Zealand Health Policy 2005, 2:27 http://www.anzhealthpolicy.com/content/2/1/27 0–16Years 40 - 69 Years F1 F1 F2 F2 F3 F3 F4 F4 F5 F5 F6 F6 F7 F7 F8 F8 F1 F1 F2 F2 F3 F3 F4 F4 F5 F5 F6 F6 F7 F7 F8 F8 100 100 100% % % 100 100 100 100% % % % 80 80 80% % % 80 80 80 80% % % % 60 60 60% % % 60 60 60 60% % % % 40 40 40% % % 40 40 40 40% % % % 20 20 20% % % 20 20 20 20% % % % 0% 0% 0% 0% 0% 0% 0% 17 - 39 Years 70 + Years 100 100% % 100 100% % 80 80% % 80 80% % 60 60 60% % % 60 60 60% % % 40 40 40% % % 40 40 40% % % 20 20 20% % % 20 20 20% % % 0% 0% 0% 0% 0% 0% M Ma ale le P Pu ub bllic ic M Ma ale le P Prriiv vat ate e IIns nsur ure ed d M Ma alle e P Prriv ivate ate U Un niins nsur ured ed Fem Fema ale le P Pu ub bllic ic F Fe em ma ale le P Prriiv vat ate e IIns nsu urred ed F Fe em ma alle e P Prriv ivat ate e U Un niins nsur ured ed Th Figure 3 e eight federal cut points overlaid on trend line data for gender and age group The eight federal cut points overlaid on trend line data for gender and age group. Stage 3: Outcome of the significance testing Quantification of the rates of change associated with Characterisation of those policies deemed to have had an inflections impact was undertaken depending upon the results of the So as to investigate in more detail changes in utilisation associated with observed inflections a separate analysis significance testing. A non-significant difference between series points 2 and 3 (p value greater than 0.05) resulted was conducted quantifying changes in the rate of change in the policy being deemed as an inhibitory policy (type of the annual proportion of episodes associated with the 3). However, a significant difference between series points introduction of those policies identified in stage 1 as 2 and 3 (p value less than or equal to 0.05) required the showing an observable inflection. This was achieved by classification of the direction of the inflection to be inte- representing each segmented trend segment as a straight grated into the analysis. line having the following mathematical properties y = a+bx (where 'a' is the intercept and 'b' is the slope). This Stage 4: Integration of the classification of the inflection analysis was carried out for trend segments 1 and 2 (see Those policy changes associated with inflections classified figure 2). Differences in the rate of change (slope of the by stage one as direction changing were subsequently trend segment expressed as percentage change per year) termed direction changing policies (type 1). While those for all payment classifications by gender and age group policy changes associated with inflections classified by were calculated stage one as magnitude changing were subsequently termed magnitude changing policies (type 2). Results Figure 3 shows the temporal positions of the eight federal health care policy cut points overlaid on the segmented Page 4 of 9 (page number not for citation purposes) 1 1980 980 19 198 80 0 19 198 85 5 1 1985 985 199 1990 0 1990 1990 19 199 95 5 1995 1995 200 2000 0 20 2000 00 19 1980 80 1980 1980 1980 19 1985 85 19 19 1985 85 85 19 1990 90 1990 1990 1990 19 1995 95 1995 1995 1995 2000 2000 2000 2000 2000 Australia and New Zealand Health Policy 2005, 2:27 http://www.anzhealthpolicy.com/content/2/1/27 Table 2: The rates of change of the proportion of public and private insured episodes pre and post federal cut points 2 (Medicare) and 8 (Lifetime Health Cover). Age Group Gender Payment Rate of change in proportion Change of Difference in Rate Classification (% change in 1 year) Direction (% change in 1 year) Federal cut point 2 1982–83 1983–84 0–16 years M Public 2.14 22.45 NO 20.312 F 2.60 19.73 NO 17.135 M Private Insured -2.99 -20.32 NO 17.333 F -3.35 -17.65 NO 14.296 17–39 years M Public 4.27 22.82 NO 18.549 F 3.10 15.83 NO 12.730 M Private Insured -5.17 -18.88 NO 13.709 F -3.87 -14.46 NO 10.590 40–69 years M Public 1.38 14.87 NO 13.489 F 1.88 10.52 NO 8.647 M Private Insured -1.99 -13.35 NO 11.362 F -2.44 -9.45 NO 7.002 70+ years M Public 0.17 5.96 NO 5.797 F 1.40 2.80 NO 1.401 M Private Insured -0.68 -5.35 NO 4.674 F -1.91 -2.28 NO 0.370 Federal cut point 8 1998–99 1999–00 0–16 years M Public 0.90 -2.49 Yes 3.398 F 0.74 -1.95 Yes 2.691 M Private Insured -1.13 3.09 Yes 4.219 F -1.06 3.08 Yes 4.143 17–39 years M Public 0.35 -1.85 Yes 2.196 F 1.44 -1.03 Yes 2.475 M Private Insured -0.43 2.81 Yes 3.232 F -1.69 1.98 Yes 3.672 40–69 years M Public 2.04 -2.74 Yes 4.787 F 2.12 -1.01 Yes 3.129 M Private Insured -2.17 3.20 Yes 5.362 F -1.97 1.63 Yes 3.608 trend lines of the proportions of annual episodes in each Federal policy initiatives that were associated with major payment classification in each age group in males and rate changes or inflections in the trend lines were federal females. cut points 2 (the re-introduction of free public hospital care via Medicare) and 8 (Lifetime Health Care). Federal Observation and quantification in changes in trend cut point 2 was associated with acceleration in the rate of In general the shape of the trends was similar in males and decline in the proportion of privately insured episodes females. In some age groups, particularly the 17–39 years and a greater rate of increase in the proportion of public age group, there was a near-constant difference in propor- episodes in all four age groups. tion between the genders. Given this finding to simplify the analysis the genders were combined. The shape of the Federal cut point 8 was another major inflection point segmented trend lines; however, varied significantly associated with a surge in the private insurance payment across age groups, with the two younger age groups expe- classification in all except the oldest age group. For the riencing the largest changes in payment classification younger three age groups the shift in direction was of sim- mainly over the early part of the observation period. The ilar magnitude as shown in table 2. The magnitude of the oldest age group had the least annual differences and a change in rates associated with the introduction of Life- more stable overall trend. time Health Cover was smaller in absolute terms, as well Page 5 of 9 (page number not for citation purposes) Australia and New Zealand Health Policy 2005, 2:27 http://www.anzhealthpolicy.com/content/2/1/27 Table 3: Federal cut points associated with significant (p < 0.05) changes in the proportion of episodes and inflections or substantial changes in trend by age group Federal Healthcare Policy Cut Points Age Group Public Private Insured Private Uninsured Age 0–16 yrs 2,5,6,8 2,5,8 2 Age 17–39 yrs 2,3,5,7,8 2,3,7,8 8 Age 40 – 69 yrs 2,4,5,7,8 2,4,5,7,8 2,8 Age 70+ yrs 2,6 2,6 Shaded areas = no cut points associated with significant changes and inflections or trend changes for the age group/couplet type combination as in the opposite direction to that associated with the Characterisation of policy effects introduction of Medicare. Four types of policies were identified by the policy charac- terisation model. Those that had no effect; type 1, those Less marked changes in the trends, in addition to the that affected the direction of the trend; type 2, those that major ones described above, were observed to coincide affected the magnitude of the trend, but not its direction; with all federal cut points to some degree, although none and type 3, those that inhibited the trend (the pre policy was seen consistently in all combinations of payment trend was positive or negative, but significance testing classification and age group. The largest of these minor indicated no-significant difference in the proportions post rate changes was associated with federal cut point 3 (see policy). It should be noted that type 3 policies prevented table 1) in the youngest age group. These changes (or subdued) a pre-existing trend from continuing. The involved inflections in the segmented trend lines with results of the characterisation of federal policies from absolute differences slightly in excess of 3.5 percent per 1980 to 2001 related to age group are detailed in table 5. year. The remaining observable changes ranged from 2.3 percent to 0.7 percent per year. Discussion In free markets consumers and suppliers are left alone to Significance testing in those cut points deemed to be interact and balance supply and demand for services. It is associated with inflections generally accepted that governments need to intervene in Significance tests of the equivalence of the proportion of health markets to provide certain services and regulate the episodes one year prior to and in the year of implementa- market. This intervention occurs via specific policy action tion for federal policy cut points associated with observa- [11]. In Australia the Commonwealth Government's deci- ble inflections are summarized in tables 3 and 4. Most sion to subsidise PHI has meant that it has increased its federal policy initiatives that showed an observable stake in the private sector alongside its existing stake in the change in trend were also associated with a significant public sector. change (p < 0.05) in private: public mix. The most notable exception to this occurred in the elderly age group. In Controversy has raged about the success of the Common- those aged 70+ years, cut points 7 (designed to increase wealth Government's policies with regard to supporting the proportion of persons holding private health insur- PHI in order to reduce the pressure on the public sector. ance by making it more affordable) was not associated The major debate has centered around the effectiveness of with a significant difference. the 30% rebate and more recently the effectiveness of the Lifetime Health Care policy [4,7,8,2-15]. However, in The privately uninsured payment classification was the most cases, commentators have used evidence relating to least affected by policy changes over time. However, the the changing prevalence of PHI membership, pre and post two most influential policies, being the introduction of policy implementation. This may not be an accurate Medicare (cut point 2) and Lifetime Health Cover (cut method to assess the effectiveness of such policies, point 8), were both associated with significant reductions because the policies themselves may promote the uptake in the proportions of private uninsured patients in several of PHI for non-health related reasons, such as to avoid a age groups, albeit that the shifts were towards the public tax penalty in high income households (cut point 6). This and private insured payment classifications respectively. coupled with the finding that since 1998 the proportion Once again in the oldest age group neither of these cut of PHI fund members with high front-end deductibles has points was associated with a significant difference. significantly increased [4] means that uptake of PHI may Page 6 of 9 (page number not for citation purposes) Australia and New Zealand Health Policy 2005, 2:27 http://www.anzhealthpolicy.com/content/2/1/27 Table 4: Federal cut points associated non-significant (p > 0.05) changes in the proportion of episodes and inflections or substantial changes in trend by age group Federal Healthcare Policy Cut Points Age Group Public Private Insured Private Uninsured Age 0–16 yrs 33,68 Age 17–39 yrs 2,5 Age 40 – 69 yrs Age 70+ yrs 77 2 Shaded areas = no cut points associated with non-significant changes and inflections or trend changes for the age group/couplet type combination not necessarily lead to the expected changes in use of the oldest age group, with no effect observed in the youngest public and private systems. This is quite apart from the age group. Thus the 30% rebate appears to have had the debate about the price elasticity of demand for PHI and desired effect on PHI use (ie reducing the pressure on the the assumption that demand for hospital care is a fixed public system) in the oldest age group, but no immediate commodity [4]. Our study has developed and used a pol- desired effect in the younger age groups. To some extent icy characterisation model based on measuring shifts in this can be explained because younger members are not as the actual use of PHI at the time of receiving hospital serv- likely to be hospitalised compared with older members, ices. This may be a more appropriate methodology for thus reducing the likelihood of an immediate effect on evaluating likely changes in the pressure on the public sys- use. While older Australians are not only more likely to be tem affected by particular policies. hospitalised and therefore have more opportunity to use PHI, but are also more likely to be attracted to purchase The results of our analysis indicate that federal cut point PHI due to reduced cost because the price elasticity of PHI 2, the re-introduction of free public hospital care via is different for younger and older individuals. Medicare, was a magnitude changing policy. This was an unexpected finding since it has been previously assumed Limitations of the model that the introduction of Medicare, following on from an For practical reasons the immediate effects of the policies era when free public hospital care was abolished, would were the only effects able to be characterised by our model be a direction changing policy. However, our data indicate due to the plethora of federal health care policy changes, that a reversal in trend in favour of the public system especially from 1993 onwards. To try to characterise the occurred one year prior to the introduction of Medicare. changes in trends over an extended period would have Federal cut point 8, Lifetime Health Cover, was classified resulted in evaluation of the mix of effects produced by by our model as a direction changing policy in the more than one policy. This is especially relevant when younger three age groups with no effect observed in the examining the effects of the 30% rebate and Lifetime oldest age group (individuals born prior to 1 July 1934 are Health Cover, where only one year separated the two pol- exempt from Lifetime Health Cover). This finding was icy changes. thus consistent with the objective of the policy, which was to reverse the declining trend in possession and use of PHI A second limitation of this policy characterisation method to reduce the burden on the public system. It would is that it cannot accurately take into account enforced appear that this was achieved immediately post-imple- waiting periods, which are mandatorily applied to indi- mentation. viduals taking out PHI who have a previous history of an illness or condition. Thus some underestimation of the The effects of the 30% rebate (federal cut point 7) on lev- effects of policies may be inherent in the model. Extend- els of PHI have been one of the most hotly contested ing the model over two years post policy initiation is political issues surrounding heath care policy in recent problematic, as discussed above, because the effect times. Commentators have argued for and against this observed would then be confounded by subsequent pol- policy initiative mainly on a cost-benefit platform [4, 12, icy changes. Another issue to be taken into account is the 14, 16]. Our analysis found that the effect of federal cut timing and extent of marketing of the policy to the public point 7 was related to age. This policy was associated by government and the private insurance industry. In the immediately in time with a change in the magnitude of case of Lifetime Health Cover, exhaustive marketing, the the existing negative trend (PHI) or a negative to positive 'Run for Cover Campaign', was undertaken over several change of direction (public) in the middle two age groups, months leading up to its implementation. It is reasonable and an inhibitory effect on the downward trend in the to assume that changes in behaviour, in this case purchas- Page 7 of 9 (page number not for citation purposes) Australia and New Zealand Health Policy 2005, 2:27 http://www.anzhealthpolicy.com/content/2/1/27 Table 5: Classification of federal policy effects on trends in age group related annual proportion of episodes by payment classification Federal Age Group cut point 0 – 16 Years 17 – 39 Years 40 – 69 Years 70+ Years Public Private Private Public Private Private Public Private Private Public Private Private Insured Uninsured Insured Uninsured Insured Uninsured Insured Uninsured F1 No trend data available prior to 1980* F2 Type 2 Type 2 Type 2 Type 2 Type 2 Type 3 Type 2 Type 2 Type 2 Type 2 Type 2 Type 3 F3 Type 3 Type 3 Type 2 Type 2 F4 Type 1 Type 1 F5 Type 2 Type 2 Type 1 Type 3 Type 2 Type 2 F6 Type 1 Type 3 Type 1 Type 1 F7 Type 1 Type 2 Type 1 Type 2 Type 3 Type 3 F8 Type 1 Type 1 Type 3 Type 1 Type 1 Type 1 Type 1 Type 1 Type 1 * Since no data was available about the trend 1979–1980 the classification of this policy was not possible. However, in the known historical setting sudden removal of free public hospital care it would be most likely that this policy was a type 1 (direction changing). Type 1: Direction changing, Type 2: Magnitude changing, Type 3: Inhibitory Shaded areas indicate no observable effect from the policy change. ing of PHI, were likely to have been made prior to the pol- with an immediate increase in patients in hospital using icy implementation date, thus some of the waiting period, PHI. While the 30% rebate for PHI introduced 18 months if applicable, would have been served prior to the policy earlier did not have an immediate desired effect, the limi- implementation date. Conversely, advantage could be tations of the model are such that we cannot be certain taken of the 30% rebate at any time after, but not before what, if any, latent contribution to the change in private: January 1999. The net result of these two limitations on public mix may have occurred. From this study we con- our policy characterisation model may be that of cancel- clude that an outcome-based policy characterisation ling each other out in the case of Lifetime Health Cover model is useful in evaluating immediate effects of changes and causing a latent period between cause and effect in in health care policy. the case of the 30% rebate. Competing interests In addition, it could be argued that since the waiting Professor D'Arcy Holman is an independent director of period only applies to pre-existing conditions, those wish- HBF Health Funds inc which is the largest provider of pri- ing to use newly acquired PHI for such a condition would vate health insurance in Western Australia. be doing so to facilitate a more expedient health interven- tion than could be achieved in the public sector. As such Authors' contributions these episodes of care would not normally have been The manuscript has been read and approved by all authors and the requirements for authorship have been observed in the public system over the same period, but rather at a later time. Under these circumstances the wait- met as outlined below. REM was responsible for the con- ing time for benefits may serve to enhance the validity of ception and design of the study; analysis and interpreta- a characterisation model employing a latent period. tion of the data; and drafting and revising the paper. CDJH was responsible for conception and design of the Finally, our policy characterisation model does not allow study; interpretation of the data; and revising the paper. for the possibility of an earlier policy initiative synergising with a subsequent initiative. Thus it is possible that the Acknowledgements The initial construction of the Data Linkage System was funded by the immediate effect of Lifetime Health Cover may have been Western Australian Lotteries Commission. This study was undertaken as a less potent in the absence of the pre-existing 30% rebate. part of a Collaborative Research and Development Venture funded by HBF Health Funds Inc and the WA Department of Health. We would also like Conclusion to thank the WA Department of Health for on-going support of the Data Our study has developed and applied a policy characteri- Linkage Unit. sation model based on measuring shifts in use of PHI immediately prior to, and immediately following imple- References mentation of changes in federal health care policy. Our 1. Sullivan N, Redpath R, O'Donnell A: Public Hospitals: Who's looking after you? The Difficulties in Encouraging Patients to use their Private results indicate that Lifetime Health Cover was associated Page 8 of 9 (page number not for citation purposes) Australia and New Zealand Health Policy 2005, 2:27 http://www.anzhealthpolicy.com/content/2/1/27 Health Insurance in Public Hospitals. Australian Health Review 2002, 25:6-14. 2. Willcox S: Promoting Private Health Insurance in Australia. Health Affairs 2001, 20:152-161. 3. Duckett SJ: The Australian Health Care System. Oxford, Oxford University Press; 2000. 4. Deeble J: The Private Health Insurance Rebate: Report to State and Territory Health Ministers. , National Centre for Epi- demiology and Population Health The Australian National University; 5. McAuley IA: Stress on public hospitals - why private insurance has made it worse. University of Canberra, Discussion paper: Aus- tralian Consumers' Association and the Australian Healthcare Asso- ciation; 2004. 6. Duckett SJ, Jackson TJ: The New health Insurance Rebate: An Inefficient Way of Assisting Public Hospitals. Medical Journal of Australia 2000, 172:439-442. 7. Butler J: Policy Change and Private Health Insurance: Did the Cheapest Policy do the Trick? Australian Health Review 2002, 25:33-41. 8. Cormack M: Private Health Insurance: The Problem Child Faces Adulthood. Australian Health Review 2002, 25:38-51. 9. National Network of Libraries of Medicine: Define Measurable Goals, Outputs and Outcomes. [http://nnlm.gov/libinfo/commu nity/goals.php]. 10. Holman CDJ, Bass AJ, Rouse IL, Hobbs MST: Western Australia: Development of a Health Services Research Linked Data- base. Aust NZ J Public Health 1999, 23:453-459. 11. Whiteford H: Can Research Influence Mental Health Policy? Australian and New Zealand Journal of Psychiatry 2001, 35:458-434. 12. Australian Health Insurance Association: AHIA Submission on PHI Reforms to Senate Legislation Committee: Health Leg- islation Amendment (Private Health Insurance Reform) Bill 2003. Volume 2004. , AHIA; 2003. 13. Harper I: Preserving ChoiceA defence of public support for private health care funding in Australia. Medibank Private 2003. 14. Econtech Pty Ltd, Harper Associates, Hagan P: Easing the Pres- sure: The Intergenerational Report and Private Health Insurance. , Medibank Private; 2004. 15. Access Economics: Striking a Balance: Choice, Access and Affordability in Australian Health Care. , APHA; 2002. 16. Segal L: Why it is time to review the role of private health insurance in Australia. Australian Health Review 2004, 27:3-14. Publish with Bio Med Central and every scientist can read your work free of charge "BioMed Central will be the most significant development for disseminating the results of biomedical researc h in our lifetime." Sir Paul Nurse, Cancer Research UK Your research papers will be: available free of charge to the entire biomedical community peer reviewed and published immediately upon acceptance cited in PubMed and archived on PubMed Central yours — you keep the copyright BioMedcentral Submit your manuscript here: http://www.biomedcentral.com/info/publishing_adv.asp Page 9 of 9 (page number not for citation purposes)

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Published: Nov 8, 2005

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