Cost-Effectiveness of Diabetes Pay-for-Performance Incentive Designs

Cost-Effectiveness of Diabetes Pay-for-PerformanceIncentive Designs

Hui-Min Hsieh, PhD,* Shu-Ling Tsai, PhD,w Shyi-Jang Shin, MD, PhD,z

Lih-Wen Mau, MPH, PhD,y and Herng-Chia Chiu, PhD8z

Background: Taiwan’s National Health Insurance (NHI) Program

implemented a diabetes pay-for-performance program (P4P) based

on process-of-care measures in 2001. In late 2006, that P4P program

was revised to also include achievement of intermediate health

outcomes.

Objectives: This study examined to what extent these 2 P4P in-

centive designs have been cost-effective and what the difference in

effect may have been.

Research Design and Method: Analyzing data using 3 population-

based longitudinal databases (NHI’s P4P dataset, NHI’s claims

database, and Taiwan’s death registry), we compared costs and

effectiveness between P4P and non-P4P diabetes patient groups in

each phase. Propensity score matching was used to match com-

parable control groups for intervention groups. Outcomes included

life-years, quality-adjusted life-years (QALYs), program inter-

vention costs, cost-savings, and incremental cost-effectiveness

ratios.

Results: QALYs for P4P patients and non-P4P patients were 2.08

and 1.99 in phase 1 and 2.08 and 2.02 in phase 2. The average

incremental intervention costs per QALYs was TWD$335,546 in

phase 1 and TWD$298,606 in phase 2. The average incremental all-

cause medical costs saved by the P4P program per QALYs were

TWD$602,167 in phase 1 and TWD$661,163 in phase 2. The

findings indicated that both P4P programs were cost-effective and

the resulting return on investment was 1.8:1 in phase 1 and 2.0:1 in

phase 2.

Conclusions: We conclude that the diabetes P4P program in both

phases enabled the long-term cost-effective use of resources and

cost-savings regardless of whether a bonus for intermediate out-

come improvement was added to a process-based P4P incentive

design.

Key Words: diabetes pay-for-performance, incentive designs, cost-

effectiveness analysis (CEA), quality-adjusted life-years (QALYs),

incremental cost-effectiveness ratios (ICERs)

(Med Care 2015;53: 106–115)

Public and private payers of health care services in manycountries are seeking ways to invest less money on the

payment of incentives while improving quality in health careefficiently. Pay-for-performance (P4P) or value-based pur-chasing has been considered by several countries as a meansof this.1–6 P4P is a payment model in which financial in-centives are paid to health care providers for reachingpredefined performance targets.1,7–9 Designing and im-plementing a successful P4P program is complex.1,9,10 Inmost P4P schemes, financial incentives have been grantedbased on the performance of predefined process indicators(ie, whether or not specified services have been performed)or outcome indicators (ie, whether or not a health outcomehas been achieved).8,11 Although design features may playimportantly into whether goals are reached, there has beenvery little research on the cost-effectiveness of specific de-sign features changes in a P4P program, which could helpserve as a guide for public or private payers.12,13

A P4P can be considered cost-effective when quality isimproved at equal or lower costs. Studies on the cost-ef-fectiveness of P4P are scarce and inconclusive.12,14,15 Mosthave focused on the quality improvements of P4P schemes,but have neglected their cost and cost-effectiveness.1,8,12,14,16

This knowledge gap has been noted by a number of re-views.1,8,12,14,16 Few studies have attempted to estimatecost-effectiveness using full economic evaluations [eg,quality-adjusted life-years (QALYs)].14,16 One study byNahra et al17 conducted a cost-utility analysis from an in-surer’s perspective to investigate the cost-effectiveness of aP4P program designed to improve the quality of health carein hospital settings in the United States. That study lacked a

From the *Department of Public Health, Kaohsiung Medical University,Kaohsiung, Taiwan; wNational Health Insurance Administration,Ministry of Health and Welfare, Taipei; zDivision of Endocrinology andMetabolism, Graduate Institute of Medical Genetics, College of Medi-cine, Kaohsiung Medical University, Kaohsiung Medical UniversityHospital, Kaohsiung, Taiwan; yNational Marrow Donor Organization,Edina, MN; 8Department of Healthcare Administration and MedicalInformatics, Kaohsiung Medical University; and zDepartment of Busi-ness Administration, National Sun Yat-Sen University, Kaohsiung,Taiwan.

Supported by DOH Grant (DOH101-NH-9018): “Evaluation of Pay-for-Performance and Establishment of Prospective Payment for IntegratedCare,” awarded by the National Health Insurance Administration of theMinistry of Health and Welfare in Taiwan.

The authors declare no conflict of interest.Reprints: Herng-Chia Chiu, PhD, Department of Healthcare Administration

and Medical Informatics, Kaohsiung Medical University, 100 Shin-Chuan 1st Road, Kaohsiung 80708, Taiwan. E-mail: [email protected].

Supplemental Digital Content is available for this article. Direct URL cita-tions appear in the printed text and are provided in the HTML and PDFversions of this article on the journal’s Website, www.lww-medicalcare.com.

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ORIGINAL ARTICLE

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control group and overlooked the possibility that the resultsfrom the first year (the comparison year) were already in-fluenced by P4P, and thus it was unclear whether improve-ments would have been observed without P4P.14,17 A recentstudy by Meacock et al16 used QALYs, readmissions, andhospital length of stay as outcome variables in a study ofcost-effectiveness of a P4P program in England amonghospitals participating in P4P and those not participating inthe program over a 18-month period, and they found theprogram to be a cost-effective based on these outcomemeasures. Tan and colleagues recently conducted a cost-utility analysis from a single-payer perspective to investigatewhether a diabetes P4P program was cost-effective during2004–2005 in Taiwan. Although that study used propensityscore matching (PSM) to generate comparable case-controldatasets, the study was limited by a small sample size and itscollection of short-term data only.18 To date, no study hascompared the cost-effectiveness of 1 P4P incentivizedprocess indicators only with another that incentivizedprocess indicators and outcome indicators at the same time.The results of such a study could help in future programdevelopment.

The purpose of this study is to investigate whether 2different diabetes P4P financial metric designs, 1 im-plemented by Taiwan’s National Health Insurance (NHI)Program in 2001 based on process-of-care measure and theother late 2006 based on the addition of intermediate out-comes, allowed for a cost-effective use of resources froma single-payer perspective and to what extent their cost-effectiveness differed. We conducted a quasiexperimentaldesign of the intervention and comparison groups usingpopulation-based longitudinal NHI claims data for a2002–2006 period and a 2007–2011 period, which spannedpreimplementation and postimplementation of a reform inNHI’s diabetes P4P program incentive scheme introduced inlate 2006. The first objective was to examine the cost-ef-fectiveness of P4P in each phase, and the second objectivewas to investigate the incremental gains in cost-effectivenessresulting from the inclusion of intermediate health outcomes.

METHODS

Brief of Taiwan’s Diabetes P4P ProgramIn 1995, the government of Taiwan launched a uni-

versal compulsory NHI system, which by 2012 providedhealth coverage for 99.6% of the total population ofTaiwan’s residents (23 million). Diabetes mellitus was thefifth leading cause of death in 2012 and accounted for thedeath of 4.47% in Taiwan’s total population, a rate that hadquickly increased to 6.38% by 2008.19 In 2011 Taiwan’sNHI reported that 4.5% of the nation’s total health ex-penditures were devoted to the treatment of diabetes,20 anindication that diabetes is a very serious disease there andrapidly increasing in prevalence.

In an effort to improve quality of care for diabetespatients efficiently, the NHI initiated a diabetes P4P programin the end of 2001. This program consists of several im-portant features. For example, physicians who specialized inmetabolic disorders or endocrinology or those who had

participated in a training program for diabetes shared carewere eligible to participate in and voluntarily enroll patientsinto this special P4P for diabetes care.21–23 The physiciansand medical care staff members at the various hospitals andclinics are expected to work as a coordinated physician-ledmultidisciplinary team adhering to clinical guidelines es-tablished for the care of diabetes patients.23 All participatingproviders are mandated to submit follow-up reports andclaims data to Taiwan’s NHI for reimbursement.

The financial incentive schemes in this program wererevised at 2 point. This created 2 periods marked by differentquality incentive metrics designs.21,22 From 2001 to the end of2006, financial incentives were paid for process-of-care servicesonly (eg, documented provisions of HbA1c or low-densitylipoprotein tests). That provision of care included medicalhistory assessment, physical examination, laboratory evalua-tion, management plan evaluation, and diabetes self-manage-ment health education.21,23,24 The participating P4P physiciansreceived an extra TWD$450 (USD$15) additional to regularphysician fees, TWD$1845 (USD$60) per initial enrollmentvisit, TWD$875 (USD$30) per follow-up visit, and TWD$2245(USD$75) per annual evaluation visit. This quality incentivemetrics design remained unchanged until the end of 2006. Toencourage providers focused on the clinical outcome, the NHIadded the payment of rewards for the achievement of inter-mediate outcomes to the incentives they were already payingfor process-of-care in late 2006. A composite score for eachparticipated physician is calculated based on the average ofthese intermediate outcome indicators using equal weightsamong his or her patients. Clinical outcome measures for cal-culating composite scores included 2 negative outcomes (ie,percentage of HbA1c > 9.5% and percentage of low-densitylipoprotein > 130 mg/dL) and 1 positive outcome indicator(percentage of HbA1c < 7%). Physicians receive quality re-wards of TWD$1000 (USD$30) per each of completed annualfollow-up enrolled cases if their performances are rankedwithin the top 25% of the composite scores found for all par-ticipating physicians.21,22

Data SourceWe used data from 3 population-based databases

sources in Taiwan from 2001 to 2011. One database was anationwide diabetes P4P database from which we couldprecisely identify whether patients were enrolled in the P4Pprogram. Another was the NHI administrative claims data-base from which we could obtain information on patientcomorbidities and health provider characteristics. The otherwas a database containing death registry data, which pro-vides accurate death date information. This study was ap-proved by the Institutional Review Board at KaohsiungMedical University Hospital.

Study PopulationUsing nationwide NHI claims data, we included type 2

diabetes patients if he or she had a primarily diabetes diag-nosis (ICD-9-CM codes with 250.xx or A-code 181, ex-cluding 250.�1 or 250.x3) in at least 2 outpatient visits or atleast 1 inpatient hospitalization for each year in the 2001-implemented process-oriented diabetes P4P program be-

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tween 2002 and 2003, henceforth called “phase 1” or in thelate 2006-revised diabetes P4P program between 2007 and2008, henceforth called “phase 2.” Using the P4P database,we identified and enrolled P4P patients into our 2 studygroups if they were newly enrolled during the above-statedtime periods of each phase. The index date for each P4Ppatient was defined as the date that they were first enrolled inthe P4P program during the patient identification periods.Patients younger than 18 years old at index date were ex-cluded. We then identified non-P4P diabetes patients ascomparison groups if those patients were not found to beenrolled in the P4P program during those periods. Supple-mentary Figure 1 (Supplementary Digital Content, http://links.lww.com/MLR/A822) provides more informationabout study inclusion and exclusion criteria.

To address the issue of the same patient having mul-tiple outpatient visits to different health care providers, weapplied the plurality provider algorithm for assigning a non-P4P patient to the most frequently seen physician, defined asone who billed for the greatest number of care visits duringidentification period in each phase, as has been used inprevious studies.21,24,25 We directly assigned P4P patients tothe physician who enrolled them into the P4P program as themost frequently seen physician. In total, there were 8692frequently seen physicians treating 74,529 of P4P patientsand 706,567 non-P4P patients in the phase 1, and there were11,894 physicians treating 76,901 P4P patients and 826,612non-P4P patients in phase 2. About 10.55% and 9.30% ofdiabetes populations were newly enrolled in the P4P programin phase 1 and phase 2, respectively.

To avoid potential confounding by selection bias andconfounding factors, we used PSM approach to determinecomparison groups. Using a logistic regression model, wecreated propensity scores that predicted the probability ofpatients’ enrollment in the P4P program in each phase. Thecovariates included patients’ demographic characteristics(age and sex), a diabetes complication severity index(DCSI),26 a chronic illness with complexity (CIC) index.27,28

The DCSI takes into consideration 7 categories of compli-cations (identified by ICD-9-CM codes): cardiovascularcomplications, nephropathy, retinopathy, peripheral vasculardisease, stroke, neuropathy, and metabolic disorders. DCSIhas a total score of 13 points, the higher score, the moresevere the disease state. The CIC index was used to adjustfor comorbidity of patients with multiple chronic diseases.This index covers nondiabetes physical illness complexity(including cancers, gastrointestinal, musculoskeletal, andpulmonary diseases), diabetes-related complexity, and men-tal illness/substance abuse complexity. Diabetes-relatedcomplexity of CIC was not included to avoid duplicationcomorbidity-related values captured by the DCSI index.24

Following previous studies,21,24 both DCSI and CIC mea-sures were categorized into 3 categories (0, 1, and Z2). Inaddition, because the P4P program required health staffworked as a team to care patients and cost structures maydiffer in different level of health institutions, health careprovider characteristics were also included, such as accred-itation level (medical center, regional hospital, local hospital,or clinic), ownership type (public, not-for-profit, or for-

profit), and geographic location (Taipei, northern, central,southern, Kao-Ping, or eastern area), to capture the resourcesand capacities for individual health care institutions.

The PSM caliper matching method with 1 to 1 matchwas used to match intervention group members with com-parison group in each phase based on propensity score.29,30

Given that non-P4P patients lacked specific enrollment indexdates, their index date was assigned based the index date oftheir matched counterpart in their corresponding P4P group.To compare between phases and between groups, we fol-lowed each P4P and non-P4P patient in each phase for 3years from the index date. Any patient was censored if he orshe dropped out of the insurance program or had died.

Cost MeasuresWe analyzed costs from a single-payer perspective. Two

distinct types of direct medical costs were measured. The firstwas the P4P program intervention cost, which was measuredusing diabetes-related outpatient costs (DM-OPD costs).Given that the P4P programs paid physicians quality bonusesfor providing essential examinations/tests outlined by theprogram in addition to regular DM-OPD diabetes care, thedifference of DM-OPD treatment costs between P4P and non-P4P patients would be reflected in the program interventioncosts. Second, we measured cost-savings from P4P programusing 2 parameters. One was the potential cost-savings re-sulting from reduced costs in diabetes-related emergencyvisits and hospital admissions, which were measured as dia-betes-related medical costs (DM-ED/INP costs), and the otherwas all-cause medical costs with the exclusion of the DM-OPD costs. It is assumed that improved quality of carethrough regular outpatient follow-up visits would decrease therisks of any diabetes-related end point (eg, microvasculardisease, myocardial infarction, or death),31 which would inturn reduce health utilization and health expenses related toemergency visits or hospitalizations. Cost data were extractedfrom the NHI claims and adjusted to 2002 price based on theNHI global budgeting annual negotiation rate (approximately3% discount rate). Costs are presented in Taiwan Dollar(TWD). The exchange rate between TWD and USD dollars isabout 1:30 in this study.

Effectiveness MeasuresWe used patients’ life-years saved (LYs) and QALYs

as effectiveness measures because intensive diabetes caremay decrease risks of complications or death and thus in-crease LYs.31 LYs were measured from the index date tilldeath or the date of last follow-up within 3 years in thecensored data. Health-related quality of life (HRQoL) wasestimated using the generic Short-Form (SF)-12 survey in-strument, which is a multidimensional generic measure ofHRQoL for chronic care.32,33 Following previously pub-lished preference-based algorithms, the SF-12 scores wereconverted to utility weights, ranging from 0 to 1.32–34 Thehigher the utility weight, the better the HRQoL. These datawere derived from one of our working studies, which is alarge-scale nationwide cross-sectional survey of diabetespatients with and without enrollment in Taiwan’s diabetesP4P program from February to November in 2013. As shown

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in the Supplementary Table 1 (Supplementary Digital Con-tent, http://links.lww.com/MLR/A822) the total number oftype 2 diabetes in the survey was 1296 (938 P4P patients,357 non-P4P patients). Mean utility weighted from the sur-vey was used as proxy measures to capture health-relatedutility for P4P and non-P4P patients in this study. The overallutility weight for P4P and non-P4P patients in our study were0.71 ± 0.01 and 0.70 ± 0.02. QALYs were then measured bymultiplying LYs by utility weight of each patient in bothgroups for each phase.

Economic and Statistical Analytical ApproachTo answer the study questions, we conducted a cost-

utility analysis. We analyzed the costs over the 3-year periodfor each patient and discounted the effects over the expectedpatient life. We combined data for P4P and non-P4P patientsin phase 1 and phase 2 and then analyzed data using multiplegeneralized linear regressions while controlling for varia-tions between 2 P4P phases from patient characteristics andhealth care provider factors. A heteroskedasticity-robust SEadjustment was used, and patients were clustered withinhealth care institutions to control for unequal error variancesacross institutions. We then calculated incremental costs andeffectiveness by differences in these values for P4P andnon-P4P patients in each phase using adjusted predictedestimates. In addition, we calculated the incremental cost-effectiveness ratio (ICER) as the ratio of the difference incosts between groups and divided by difference in effec-tiveness in each phase and also compared the differentialeffect of ICER between 2 phases.35,36 All incrementalmeasures were adjusted by the patient demographic andclinical characteristics as well as health care institutionalcharacteristics. Bootstrapping with 100 replications withsample size equivalent to the original was used to obtain SEsfor the incremental measures.37,38 Each point of bootstrappedestimate of the adjusted incremental effectiveness and costswere generated and then plotted in an incremental cost-ef-fectiveness plane.35–37 All statistical operations were per-formed using SAS version 9.3 (SAS Institute, Cary, NC) andStata SE 12 version. A P < 0.05 was considered significant.

RESULTSTables 1 and 2 summarize baseline patient and health

care provider characteristics for the P4P and non-P4P pa-tients (prematching and postmatching) in phases 1 and 2.Before matching, we included 74,529 P4P patients and706,657 non-P4P patients in phase 1, and 76,091 and826,612 in phase 2. In both the phases, significant differ-ences were found between the prematched intervention andcomparison groups (P < 0.001) with respect to all charac-teristics assessed. After PSM matching, however, the 2groups were found to be similar in both phases.

Tables 3 and 4 report the incremental estimates andICERs by direct medical costs and QALYs for P4P and non-P4P patients in both phases. Table 3, which compares pro-gram effectiveness, intervention costs, and cost-savings forthe 2 phase groups, shows that both P4P groups receivedsignificantly more effective care (LYs and QALYs gains)

than their corresponding non-P4P groups and their cost-savings were significantly greater in both phases (bothP < 0.001). Specifically, with regard to effectiveness of care,LYs for P4P and non-P4P patients were 2.92 and 2.85 inphase 1. After multiplying utility weight by LYs, thosevalues, reinterpreted as QALYs, were 2.08 and 1.99, re-spectively. Adjusted incremental values per LYs gained was0.062 and per QALYs gained was 0.073 (P < 0.001) (Ta-ble 3). With regard to costs of intervention, the difference inadjusted incremental DM-OPD costs between P4P and non-P4P patients was TWD$24,529 (USD$818) and cost-savings,analyzed by adjusted incremental DM-ED/INP cost, wasTWD$�12,759 (USD$�425). Adjusted incremental all-cause medical cost was TWD$�44,020 (USD$�1467)(Table 3). Supplementary Appendix Table 2 (SupplementaryDigital Content, http://links.lww.com/MLR/A822) providesfull models for the analyses used to obtain Table 3 results.

Table 4, which further analyzes Table 3 data, shows that,compared with those for non-P4P patients, the ICER for cost-savings (DM-ED/INP) as well as all-cause medical costs by gainsin LYs and QALYs were significantly greater for P4P patients inboth phases (all <0.001). The ICER of intervention costs (DM-OPD) for P4P patients was TWD$335,546 (USD$11,185) perQALY gained compared with non-P4P patients in phase 1,whereas the ICER of cost-savings (ED-ED/INP) was forTWD$�174,535 (USD$�5818) per QALY gained and theICER of all-cause medical costs was TWD$�602,167(USD$�20,072) per QALY gained. In a further analysis, phase 2was found to have significantly lower intervention costs (DM-OPD) per QALY gained than phase 1 (ICER TWD$36,939 orUSD$1231 less) (P < 0.001). There was a small but significantgreater cost-savings of ICERs in all-cause medical costs(TWD$58,996 or USD$1967 less) in phase 2 (P < 0.001). Figure 1shows scatter plots for the distribution of incremental QALYs andincremental costs on the cost-effectiveness planes. That figureshows cost-savings in all-cause medical costs were about twice ofintervention costs in both phases. It also shows that phase 2 P4Pprogram had only slightly lower intervention costs and greatercost-savings in all-cause medical costs.

DISCUSSIONAlthough the use of P4P schemes has become a com-

mon component of reimbursement in health care delivery,evidence of its efficiency is still lacking.14,16,36 In this study,we evaluated the cost-effectiveness of changes in incentivedesigns in a voluntary P4P program for diabetes quality ofcare in Taiwan. Rather than relying on simulation modelingof the schemes’ consequences, we have directly estimatedthe incremental effects of costs and cost-effectiveness. Forboth phases of the P4P, we studied over 3-year long-termperiods, we observed that the P4Ps significantly increasedadjusted LYs and QALYs and made possible the cost-effective use of resources.

Specifically, we found in both phases that patientsenrolled in the P4P program had greater program inter-vention costs, but greater cost-savings in DM-ED/INP costsas well as all-cause medical costs. Previous studies have





found that, after program enrollment, P4P patients had sig-nificantly more diabetes-related outpatient visits, greaterexpense, and higher utilization of guideline-recommendedservices than non-P4P patients.18,22,24,39 One study alsofound improving trends in P4P patients’ intermediate out-comes.40 Under such conditions, it can be expected that risksof emergency visit and hospitalizations caused by any dia-betes-related complications or conditions as well as healthexpenses would decrease.18,24,31

In addition, based on results in Table 4, the averageincremental DM-OPD costs per QALYs gained wasTWD$335,546 (USD$11,185) in phase 1 and TWD$298,606(USD$9954) in phase 2, indicating the NHI had invested onthe patients the P4P program over a 3-year period, and inturn, the program saved average incremental all-causemedical costs per QALYs gained of TWD$602,167

(USD$20,072) in phase 1 and $661,163 (USD$22,039) inphase 2. The P4P programs were found to be cost-effective,providing a return on investment (ROI) of about 1.8:1–2.0:1in first and second phase, respectively. Similar results werereported by Curtin and colleagues in a study comparingoverall costs of implementing and maintaining a P4P pro-gram for a health maintenance organization’s population.Their study found the positive ROI to range 1.6 and 2.5,which led them to conclude that the P4Ps were worthy in-vestments.41

The current study found a significant but small increasein ICER per QALY gained in all-cause medical costs(TWD$�58,996 or USD$�1967) and not in DM-ED/INPcosts (Table 4) between phase 1 and phase 2. Similar resultswere found when we plotted cost-effectiveness planein Figure 1. It may be that P4P should be seen as catalyst for

TABLE 1. Baseline Patient and Health Care Provider Characteristics for P4P and Non-P4P Patients in Phase 1

Phase 1

Intervention Group Comparison Group

P4P Prematched Non-P4P Postmatched Non-P4P

Variables Mean±SD/N (%) Mean±SD/N (%) P Mean±SD/N (%) P

N 74,529 706,657 74,529Patients’ demographic characteristics

Sex [N (%)]Male 35,282 (47.34) 355,558 (50.32) < 0.001 35,331 (47.41) 0.799Female 39,247 (52.66) 351,099 (49.68) 39,198 (52.59)

Age categories [N (%)]< 45 8,498 (11.40) 82,071 (11.61) < 0.001 8,466 (11.36) 0.76245–54 18,291 (24.54) 157,664 (22.31) 18,259 (24.50)55–64 21,962 (29.47) 178,231 (25.22) 21,935 (29.43)65–74 19,598 (26.30) 187,509 (26.53) 19,648 (26.36)75+ 6,180 (8.29) 101,182 (14.32) 6,221 (8.35)

Patients’ clinical characteristicsDCSI score (mean ± SD) 1.00 ± 1.26 1.04 ± 1.40 < 0.001 0.99 ± 1.25 0.361DCSI categories [N (%)]

0 35,028 (47.00) 352,385 (49.87) < 0.001 35,109 (47.11) 0.8861 19,533 (26.21) 154,951 (21.93) 19,529 (26.20)Z2 19,968 (26.79) 199,321 (28.21) 19,891 (26.69)

CIC counts (mean ± SD) 1.16 ± 1.00 1.20 ± 1.02 < 0.001 1.15 ± 0.99 0.322CIC categories [N (%)]

0 22,115 (29.67) 201,430 (28.50) < 0.001 22,163 (29.74) 0.8391 27,256 (36.57) 253,129 (35.82) 27,316 (36.65)Z2 25,158 (33.76) 252,098 (35.67) 25,050 (33.61)

Health care institution characteristicsAccreditation level [N (%)]

Medical center 12,339 (16.56) 178,319 (25.23) < 0.001 12,416 (16.66) 0.800Regional hospital 33,983 (45.60) 189,843 (26.86) 34,017 (45.64)Local hospital 17,481 (23.46) 146,436 (20.72) 17,496 (23.48)Clinics 10,726 (14.39) 192,059 (27.18) 10,600 (14.22)

Ownership type [N (%)]Public 19,244 (25.82) 198,934 (28.15) < 0.001 19,262 (25.84) 0.924Not-for-profit 28,173 (37.80) 224,876 (31.82) 28,100 (37.70)For-profit 27,112 (36.38) 282,847 (40.03) 27,167 (36.45)

Location of health care institution [N (%)]Taipei 18,237 (24.47) 210,297 (29.76) < 0.001 18,115 (24.31) 0.963Northern 10,315 (13.84) 101,281 (14.33) 10,365 (13.91)Central 24,936 (33.46) 119,105 (16.85) 24,924 (33.44)Southern 9,093 (12.20) 119,841 (16.96) 9,156 (12.29)Kao-Ping 10,224 (13.72) 135,932 (19.24) 10,268 (13.78)Eastern 1,724 (2.31) 20,201 (2.86) 1,701 (2.28)

P-value here was to compare patient demographic and clinical characteristics and health care institutional characteristics between P4P and non-P4P patients in phase 1.CIC indicates chronic illness with complexity; DCSI, diabetes complications severity index; P4P, pay-for-performance program.



quality improving behavior that would subsequently becomeembedded into routine services. Meacock and colleaguesstated, “The intended and unintended behavioral responsesof providers have formed the main focus of most research onP4P, not whether it is cost-effective.” Our findings suggestthat P4P program led to a positive learning curve for healthcare provider’s regular follow-up care regardless whether thebonus for intermediate outcome improvement was added tothe P4P incentive design. More studies are needed to furtherexamine whether additional incentives reward contribute toP4P efficiency.

This study has several limitations. First, although wewere able to measure P4P bonuses for process outcomes inboth phases from the administrative claim data, we were un-able to estimate extra quality rewards of improving inter-mediate outcomes in phase 2 because Taiwan’s P4P program

stipulates that the extra quality rewards for intermediate out-comes be paid annually as lump-sum payments to physicians.Therefore, these rewards are not reported in the claims data.The lack of this information might have led to underestimatesthe program’s interventional costs as well as the ICER of theDM-OPD costs per QALY gains in phase 2. Second, we onlyestimated direct medical costs paid by the NHI rather thanincluding opportunity costs, indirect costs, or NHI infra-structure/administrative costs, as suggested by Meacock et al.16

Third, we observed that patients in phase 1 had more co-morbidities or more severe conditions those in phase 2, andthus they had greater health costs than those in phase 2. Giventhe fact that the participated providers voluntarily enroll pa-tients into the system based on their capacities for providingcare, patients who were younger and/or less sick may be se-lected as enrollees.21,42 To address these issues, we pooled 2

TABLE 2. Baseline Patient and Health Care Provider Characteristics for P4P and Non-P4P Patients in Phase 2

Phase 2

Intervention Group Comparison Group

P4P Prematched Non-P4P Postmatched Non-P4P

Variables Mean±SD/N (%) Mean±SD/N (%) P Mean±SD/N (%) P

N 76,901 826,612 76,901Patients’ demographic characteristics

Sex [N (%)]Male 38,478 (50.04) 425,620 (51.49) < 0.001 38,453 (50.00) 0.799Female 38,423 (49.96) 400,992 (48.51) 38,448 (50.00)

Age categories [N (%)]< 45 10,142 (13.19) 87,507 (10.59) < 0.001 10,091 (13.12) 0.76245–54 19,592 (25.48) 178,951 (21.65) 19,597 (25.48)55–64 22,462 (29.21) 217,217 (26.28) 22,458 (29.20)65–74 17,131 (22.28) 198,715 (24.04) 17,146 (22.30)75+ 7,574 (9.85) 144,222 (17.45) 7,609 (9.89)

Patients’ clinical characteristicsDCSI score (mean ± SD) 0.76 ± 1.17 1.02 ± 1.42 < 0.001 0.75 ± 1.16 0.361DCSI categories [N (%)]

0 45,265 (58.86) 426,209 (51.56) < 0.001 45,361 (58.99) 0.8861 16,095 (20.93) 172,980 (20.93) 16,083 (20.91)Z2 15,541 (20.21) 227,423 (27.51) 15,457 (20.10)

CIC counts (mean ± SD) 1.09 ± 1.00 1.14 ± 1.02 < 0.001 1.09 ± 0.99 0.322CIC categories [N (%)]

0 25,195 (32.76) 257,448 (31.14) < 0.001 25,239 (32.82) 0.8391 27,572 (35.85) 295,189 (35.71) 27,632 (35.93)Z2 24,134 (31.38) 273,975 (33.14) 24,030 (31.25)

Health care institution characteristicsAccreditation level [N (%)]

Medical center 12,650 (16.45) 195,119 (23.60) < 0.001 12,667 (16.47) 0.800Regional hospital 26,701 (34.72) 206,627 (25.00) 26,840 (34.90)Local hospital 15,376 (19.99) 147,585 (17.85) 15,356 (19.97)Clinics 22,174 (28.83) 277,281 (33.54) 22,038 (28.66)

Ownership type [N (%)]Public 17,459 (22.70) 199,847 (24.18) < 0.001 17,416 (22.65) 0.924Not-for-profit 30,336 (39.45) 262,884 (31.80) 30,353 (39.47)For-profit 29,106 (37.85) 363,881 (44.02) 29,132 (37.88)

Location of health care institution [N (%)]Taipei 25,721 (33.45) 244,997 (29.64) < 0.001 25,673 (33.38) 0.963Northern 7,491 (9.74) 119,054 (14.40) 7,507 (9.76)Central 19,164 (24.92) 141,047 (17.06) 19,132 (24.88)Southern 10,385 (13.50) 143,472 (17.36) 10,454 (13.59)Kao-Ping 11,768 (15.30) 153,872 (18.61) 11,789 (15.33)Eastern 2,372 (3.08) 24,170 (2.92) 2,346 (3.05)

P-value here was to compare patient demographic and clinical characteristics and health care institutional characteristics between P4P and non-P4P patients in Phase 2.CIC indicates chronic illness with complexity; DCSI, diabetes complications severity index; P4P, pay-for-performance program.



TA

BLE

3.

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en

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ect

sof

Med

icalC

ost

san

dQ

ualit

yof

Life

-ad

just

ed

Life

-Years

Phase

1Phase

2

Mean±

SD

Mean±

SD

Measures

P4P

(N=

74,592)

Non-P4P

(N=

74,592)

Unadjusted

Increm

ents*wz

(BootstrapSE)

Adjusted

Increm

ents*wz

(BootstrapSE)

P4P

(N=

76,901)

Non-P4P

(N=

76,901)

Unadjusted

Increm

ents*wz

(BootstrapSE)

Adjusted

Increm

ents*wz

(P4P�Non-P4P)

(BootstrapSE)

Eff

ecti

ven

ess

Lif

e-y

ears

(LY

s)2

.92

±0

.38

2.8

5±

0.5

40

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(0.0

02)

0.0

62***

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01)

2.9

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62

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0.0

54***

(0.0

02)

0.0

62***

(0.0

01)

QA

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90

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(0.0

02)

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(0.0

01)

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sy8

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51

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85

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0,4

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38

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(1,8

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01.

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TABLE 4. The Incremental Cost-Effectiveness Ratio (ICER) in Phase 1 and Phase 2

Phase 1 Phase 2 Phase 2�Phase 1

ICER Measures

Unadjusted

Increments*wz

(Bootstrap SE)

Adjusted

Increments*wz

(Bootstrap SE)

Unadjusted

Increments*wz

(Bootstrap SE)

Adjusted

Increments*wz

(Bootstrap SE)

Adjusted Difference

in Increments*y

(Bootstrap SE)

Proxy of intervention costs8

DM-OPD costs perLYs gains

406,662*** (12,573) 395,164*** (10,209) 296,219*** (14,152) 351,632*** (9,168) �43,533*** (1,780)

DM-OPD costs perQALY gains

370,620*** (7,925) 335,546*** (6,198) 236,169*** (7,252) 298,606*** (5,543) �36,939*** (1,390)

Proxy of cost-savings8z

DM-ED/INP costs perLYs gains

�172,130*** (12,898) �205,546*** (15,902) �240,269*** (17,877) �210,831*** (15,983) �5285 (3,690)

DM-ED/INP costs perQALY gains

�156,874*** (11,402) �174,535*** (13,304) �191,561*** (14,089) �179,038*** (13,384) �4503 (3,136)

All-cause medicalcosts per LYs gains

�596,265*** (27,298) �709,158*** (26,591) �713,761*** (37,599) �778,570*** (28,672) �69,412*** (8,122)

All-cause medicalcosts per QALYgains

�543,419*** (22,118) �602,167*** (20,799) �569,066 (25,828) �661,163*** (22,346) �58,996*** (6,841)

*P < 0.05.**P < 0.01.***P < 0.001.wIncremental value here presented the value of P4P minus non-P4P with-in groups.zBootstrapping SEs were obtained from predicted difference values from the multiple generalized linear regression models. 100 times replications with sample size equivalent to

the original. Covariates that were controlled were listed in the Tables 1 and 2. Please see the supplementary Supplementary Appendix Table 2 (Supplementary Digital Content, http://links.lww.com/MLR/A822) for full models. Bootstrapped SEs were in the parentheses.

yDifference in incremental value here presented the values between difference value of P4P and non-P4P in phase 2 and value of that in phase 1.8Costs were adjusted in 2002 price using the Taiwan National Health Insurance (NHI) global budget annual negotiation rate (approximately 3% discount rate). Costs are

presented in Taiwan Dollar (TWD). The exchange rate between TWD and USD dollars is about 1:30 in this study.zDM-OPD costs were not included when calculating the DM-ED/INP costs and all-cause total costs.DM-ED/INP costs indicates diabetes-related medical costs; DM-OPD costs, diabetes-related outpatient department costs; LYs, life-years; P4P, pay-for-performance program;

QALYs, quality-adjusted life-years.

Phase 1

-60000

-50000

-40000

-30000

-20000

-10000

0

10000

20000

30000

40000

.06 .065 .07 .075 .08 .085 .09

Incremental Effectiveness (QALYs)

Incr

emen

tal C

osts

(T

WD

$)

Phase 2

-60000

-50000

-40000

-30000

-20000

-10000

0

10000

20000

30000

40000

.06 .065 .07 .075 .08 .085 .09

Incremental Effectiveness (QALYs)

DM-OPD costsDM-ED/INP costs*All-cause medical costs*

*: excluding DM-OPD costs

Incr

emen

tal C

osts

(T

WD

$)

DM-OPD costsDM-ED/INP costs*All-cause medical costs*

*: exclusing DM-OPD costs

FIGURE 1. Cost-effectiveness planes for DM-OPD costs, DM-ED/INP costs and all-cause medical costs in phase 1 and phase 2.DM-ED/INP costs indicates diabetes-related medical costs; DM-OPD costs, diabetes-related outpatient department costs.





periods of data together and adjusted for patients’ baselinedemographic and clinical comorbidities and health providers’characteristics based on the assumption that all characteristicsrelated to the decision to be in P4P program whether atphysician or patient level was assumed covered by themeasured variables. Fourth, we were not able to obtain utilityscore for each patient in our large study sample from thesecondary databases. Alternatively, we used data from across-sectional survey as proxy measures for estimatingutility weights and QALYs. The utility weights for diabetespatients were similar to those of previous studies.43 Fifth,given that the NHI patient outpatient and inpatient claim datawe have were from year 2001, we were not able to identifythe earliest date of diagnosis as diabetes and to take accountfor the time since first diagnosis for each patient. Sixth, weincluded patients who newly enrolled in the diabetes P4Pprogram as case group. Those P4P patients may not sustainretention in the program during 3-year follow-up period ineach phase. Finally, the data we used were obtained fromdiabetes populations in Taiwan, so the results may not begeneralized to other P4P programs in other countries.

In conclusion, our analysis of over 10 years’ experi-ence with P4P based on “pay-for-participation” to “pay-for-improvement” in Taiwan suggests the P4P diabetes careprogram in Taiwan provided long-term cost-effective use ofresources and cost-savings from the perspective of ROI re-gardless of whether a bonus for intermediate outcome im-provement was added to a process-based P4P incentivedesign.

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Cost-Effectiveness of Diabetes Pay-for-Performance Incentive Designs