How to build and evaluate an integrated health care system for chronic patients: study design of a clustered randomised controlled trial in rural China Executing high-quality care transitions: a call to do it right. The impact of financial incentives and a patient registry on preventive care quality: increasing provider adherence to evidence-based smoking cessation practice guidelines. How to promote, improve and test adherence to scientific evidence in clinical practice Identifying predictors of high quality care in English general practice: observational study Promotion of improvement as a science Computer Physician Order Entry: Benefits, Costs, and Issues Quality of Care Is Associated with Survival in Vulnerable Older Patients A Matched-Pair Cluster-Randomized Trial of Guided Care for High-Risk Older Patients Effect of pay-for-performance incentives on quality of care in small practices with electronic health records: a randomized trial. Changes in Patient Experiences of Primary Care During Health Service Reforms in England Between 2003 and 2007 Important Elements of Outpatient Care: A Comparison of Patients' and Physicians' Opinions Interventions for enhancing medication compliance/adherence with benefits in treatment outcomes The Use of Physician Financial Incentives and Feedback to Improve Pediatric Preventive Care in Medicaid Managed Care Effects of a Quality Improvement Collaborative on the Outcome of Care of Patients with HIV Infection: The EQHIV Study Patients' perceptions of the quality of care after primary care reform: Family medicine groups in Quebec. Recorded quality of primary care for patients with diabetes in England before and after the introduction of a financial incentive scheme: a longitudinal observational study
Background While integrated health care system has been proved an effective way to help improving patient health and system efficiency , the exact behaviour model and motivation approach are not so clear in poor rural areas where health human re sources and continuous service provision are urgently needed . To gather solid evidence , we initiated a comprehensive intervention project in Qianjiang District , southwest part of rural China in 2012 . And after one-year 's pilot , we developed an intervention package of team service , comprehensive pathway and prospect ive- and performance-based payment system . Methods To testify the potential influence of payment interventions , we use clustered r and omised controlled trial , 60 clusters are grouped into two treatment groups and one control group to compare the time and group differences . Difference-in-differences model and structural equation modelling will be used to analyse the intervention effects and pathway . The outcomes are : quality of care , disease burden , supplier cooperative behaviour and patient utilisation behaviour and system efficiency . Repeated multivariate variance analysis will be used to statistically examine the outcome differences . Discussion This is the first trial of its kind to prove the effects and efficiency of integrated care . Though we adopted r and omised controlled trial to gather the highest rank of evidence , still the fully r and omisation was hard to realise in health policy reform experiment . To compensate , the design er should take efforts on control for the potential confounders as much as possible . With this trial , we assume the effects will come from : ( 1 ) improvement on the quality of life through risk factors control and lifestyles change on patient 's behaviours ; ( 2 ) improvement on quality of care through continuous care and coordinated supplier behaviours ; ( 3 ) improvement on the system efficiency through active interaction between suppliers and patients . Conclusion The integrated care system needs collaborative work from different levels of caregivers . So it is extremely important to consider the supplier cooperative behaviour . In this trial , we introduced payment system to help the delivery system integration through providing financial incentives to motivate people to play their roles . Also , the multidisciplinary team , the multi-institutional pathway and system global budget and pay-for-performance payment system could afford as a solution As a hospital practitioner , you have undoubtedly experienced the frustration of witnessing how easily the excellent care you provide can unravel as the patient goes out the door . Patients are admitted acutely ill , and largely attributed to your clinical acumen , they are discharged “ tuned up ” and stable to return home . Days later , however , you may learn that your best-laid discharge plans were not properly executed , and the patient returned with yet another exacerbation . Clearly this scenario represents a major setback for the patient and family caregivers . Possibly dismissed as another episode of “ patient noncompliance , ” such readmissions are now being recognized as system failures and reflect a discharge process that has been described as “ r and om events connected to highly variable actions with only a remote possibility of meeting implied expectations ” ( Roger Resar , MD , Senior Fellow , Institute for Healthcare Improvement ) . Once an area that received relatively little attention , transitions out of the hospital has been identified as a priority area in need of action by a confluence of recent research and national activities . Recognizing the exp and ing evidence for lapses in quality and safety , many esteemed organizations , including the Joint Commission , the Centers for Medicare and Medicaid Services and their accompanying Quality Improvement Organizations , the Institute for Healthcare Improvement , the Institute of Medicine , National Quality Forum , the Medicare Payment Advisory Committee , the American Board of Internal Medicine Foundation , the National Transitions of Care Coalition , the American College of Physicians , the Society for General Medicine , and the Society for Hospital Medicine , are currently focusing their efforts on how to optimize transitions . All have articulated the need for further clinical investigation that can offer greater insight into the nature of the problems that arise during this vulnerable period and what the potential solutions are . In this edition of the Journal of Hospital Medicine , 3 teams of investigators have responded to this need , making timely , important , and unique contributions to advance the field . Specifically , each of these articles further raises awareness that a patient ’s transition out of the hospital often unfolds quickly in a fast-paced , chaotic manner , placing many competing dem and s on clinicians , patients , and family caregivers . Not surprisingly , such competing dem and s can contribute to deficits in quality and safety . The authors of these studies all directly identify the central role of communication among clinicians as well as between patients and clinicians in ensuring successful h and offs , further affirming the Joint Commission ’s finding that inadequate communication is the leading cause of sentinel events . In this respect , E D I T O R I A BACKGROUND This study tested the effects of two organizational support processes , the provision of financial incentives for superior clinical performance and the availability of a  patient ( smoker ) registry and proactive telephone support system for smoking cessation , on provider adherence to accepted practice guidelines and associated patient outcomes . METHODS Forty clinics of a large multispecialty medical group practice providing primary care services were r and omly allocated to study conditions . Fifteen clinics each were assigned to the experimental conditions " control " ( distribution of printed versions of smoking cessation guidelines ) and " incentive " ( financial incentive pay-out for reaching preset clinical performance targets ) .  Ten clinics were r and omized to receive financial incentives combined with access to a central ized patient registry and intervention system ( " registry " ) . Main outcome measures were adherence to smoking cessation clinical practice guidelines and patients ' smoking cessation behaviors . RESULTS  Patients ' tobacco use status  was statistically significant ( P < 0.01 ) more frequently identified in clinics with the opportunity for incentives and access to a registry than in clinics in the control condition . Patients visiting registry clinics accessed counseling programs statistically significantly more often ( P < 0.001 ) than patients receiving care in the control condition . Other endpoints did not statistically significantly differ between the experimental conditions . CONCLUSIONS The impact of financial incentives and a patient registry/intervention system in improving smoking cessation clinical practice s and patient behaviors was mixed . Additional research is needed to identify conditions under which such organizational support processes result in significant health care quality improvement and warrant the investment Background Negative variation in the management of patients with the same clinical condition is frequent , and affects quality of care . Recent studies indicate that single interventions are not an effective solution . We aim to demonstrate that a multifaceted strategy can favor the introduction of research into practice , and to assess its long-term effects on a set of common medical conditions exhibiting significant negative variation at our institution . Methods The strategy , devised and agreed upon by a multidisciplinary group , was first applied to one relevant medical condition – cerebral ischemic stroke . To test its effectiveness a quasi-experimental study was conducted , comparing an intervention group with historical controls . After validation the strategy was extended to other pathologies , and its long-term effect measured using evidence -based quality indicators . Adherence to each indicator was determined prospect ively on a six-month basis for a period of at least two consecutive years . Measures are expressed as proportions with 95 % confidence intervals . Results Validation findings demonstrated that the strategy improved compliance with scientific evidence : the percentage of patients who received a CT scan within 24 hours of hospital presentation rose from 56 % to 75 % , ( χ2 = 7.43 p < 0.01 ) ; admissions to selected wards increased from 45 % to 64 % , ( χ2 = 7.81 p < 0.01 ) ; the number of physical medicine visits within 24 hours of the request grew from 59 % to 91 % ( χ2 = 14,40 p < 0.001 ) . Over a four-year period the program was gradually applied to 14 medical conditions . Except for 3 cases , compliance with the pathway , i.e. number of eligible patients for whom data on the care process is collected , was above the minimum requirement of 75 % . Indicator adherence generally exhibited a positive trend , though variability was observed both among different conditions and between different semesters for the same pathology . Conclusion According to our experience , incorporation of research into practice can be favored by systematic ally applying a shared , multifaceted strategy , involving multidisciplinary teams supported by central coordination . Institutions should device a tailor-made approach , should train personnel on implementation strategies , and create cultural acceptance of change . Just like for experimental trials , human and economic re sources should be allocated within health care services to allow the achievement of this objective Abstract Objectives : To assess variation in the quality of care in general practice and identify factors associated with high quality care . Design : Observational study . Setting : Stratified r and om sample of 60 general practice s in six areas of Engl and . Outcome measures : Quality of management of chronic disease ( angina , asthma in adults , and type 2 diabetes ) and preventive care ( rates of uptake for immunisation and cervical smear ) , access to care , continuity of care , and interpersonal care  ( general practice assessment survey ) . Multiple logistic regression with multilevel modelling was used to relate each of the outcome variables to practice size , routine booking interval for consultations , socioeconomic deprivation , and team climate . Results : Quality of clinical care varied substantially , and access to care , continuity of care , and interpersonal care varied moderately . Scores for asthma , diabetes , and angina were 67 % , 21 % , and 17 % higher in practice s with 10 minute booking intervals for consultations compared with practice s with five minute booking intervals . Diabetes care was better in larger practice s and in practice s where staff reported better team climate . Access to care was better in small practice s. Preventive care was worse in practice s located in socioeconomically deprived areas . Scores for satisfaction , continuity of care , and access to care were higher in practice s where staff reported better team climate . Conclusions : Longer consultation times are essential for providing high quality clinical care . Good teamworking is a key part of providing high quality care across a range of areas and may need specific support if quality of care is to be improved . Additional support is needed to provide preventive care to deprived population s. No single type of practice has a monopoly on high quality care : different types of practice may have different strengths . What is already known on this topic Quality of care varies in virtually all aspects of medicine that have been studied Most studies look at quality of care from a single perspective or for a single condition What this study adds Quality of care varies for both clinical care and assessment s by patients of access and interpersonal care Practice s with longer booking intervals provide better management of chronic disease ; preventive care is less good in practice s in deprived areas No single type of practice has a monopoly on high quality care — small practice s provide better access but poorer diabetes care Good team climate reported by staff is associated with a range of aspects of high quality The remarkable achievements of modern health care make the defi ciencies associated with delivery of care all the more noticeable . Health care is a major source of avoidable harm , and patients are routinely exposed to wide and inexplicable variations in the quality of care that they receive . These variations are very diffi cult to address , despite good intentions , policy focus , ambitious improvement programmes , and investment of re sources . A major reason for this diffi culty is that the urge to act can easily overwhelm the need for evidence to inform that action , to the extent that much quality improvement work is unscientifi c — it is neither informed by high- quality evidence , nor is it subject to rigorous assessment to establish its eff ectiveness , costs , and risks . Ironically , this absence of a scientifi c approach might lead to outcomes that are exactly the opposite of what is intended by improvement eff orts : re sources can be wasted , energy and enthusiasm are dissipated , the side-eff ects of interventions are ignored , and little positive change is evident . Adoption of a more scientifi c approach to improvement has great potential to enhance the ability of health systems to provide high- quality care and optimise re source use . We believe that the science of improvement is in what Kuhn calls the pre-paradigm phase of the emergence of a new discipline , one of the characteristics of which is the absence of an agreed defi nition . Attempts to create a defi nition can trigger intense debate , and the term improvement science has so far eluded consensus . Don Berwick and the Institute of Healthcare Improvement in Boston ( MA , USA ) have infl uenced one of the most common uses of this term , which is to describe applications of the approach developed by W Edwards Deming to reduce variation in industrial processes . The quality improvement move ment associated with these methods has made a valuable contribution , not least in challenging overly techno cratic , managerialist , or regulatory-focused approaches to change . However , this conceptualisation of a science of improvement is , by itself , too narrow and restrictive to address the challenges that face the health sector , and too often under-emphasises robust assessment . Percep tion of improvement solely in terms of imple mentation and comparative eff ectiveness research is similarly inadequate . An example of a benefi t of a broader way of thinking is the reduction of central line bloodstream infections in intensive-care units . These infections are a substantial and expensive clinical problem , and are often fatal . A cohort study of 103 intensive-care units in Michigan , USA , showed that a multicomponent programme of evidence -based technical interventions , adaptive interventions targeting culture and systems , and a central ised data collection and feedback system result ed in a substantial reduction in rates of these infections . These reductions were sustained over time and were associated with reduced mortality in participating intensive-care units compared with control units . The results have been replicated in 22 additional US states . Follow-up work investigated the mechanisms through which the programme worked , and generated a theory of change that could inform , and be tested in , subsequent repe titions of the programme . Another example of a benefi t of this broader way of thinking is the increase in identifi cation and referral of victims of domestic violence . Domestic violence is often managed inadequately , despite the major health and social implication s of unidentifi ed and unmanaged abuse . In a cluster-r and omised controlled trial in 51 primary care clinics in two UK cities ( London and Bristol ) , investigators tested a range of evidence -based interventions to increase rates of primary care identifi cation and referral to specialist advocacy services of women subjected to domestic violence . The results showed three-times more recorded disclosures of domestic violence and a 22-times higher number of referrals to specialist services in the intervention group . The interventions , in the form of targeted educational programmes , are now being adopted in several places in Engl and . These examples show some distinguishing features of a broader defi nition of improvement science . Improvement science aims to create practical learning that can make a timely diff erence to patient care . It is characterised by its large domain of interest , its applied nature , and its commitment to generation of practical learning that can be applied in real-life situations . Improvement science recognises and integrates many contributions , similar to the way that engineering science uses scientifi c knowledge and theories to address real-life problems . Improvement science also aims to generate local wisdom and generalisable or transferable knowledge , with robust , well established research methods applied in highly pragmatic ways . Improvement science enables local improvement and , crucially , produces knowledge with external validity . Thus , work classifi ed as improvement science should be of suffi cient quality to be published as a long-lasting , widely disseminated record in well-respected journals . Development of local knowledge based on a strong sense of ownership and a willingness to adapt improvement activities is clearly important , but too many quality improvement projects rely on contemporaneous , non-st and ardised , unverifi ed data to make judgments about their eff ectiveness . By contrast , the science of improvement is , based on moral and practical requirements , characterised by its commitment to rigorous and credible assessment methods Lancet 2013 ; 381 : In 1998 , the Institute of Medicine 's ( IOM 's ) National Roundtable on Health Care Quality noted that the quality of health care in the United States has substantial problems and that the problems will be addressed only through profound changes to the current health care system ( 1 ) . The recent IOM report ( 2 ) , Crossing the Quality Chasm , contained an unsettling list of studies documenting the prevalence of poor- quality care in the United States . Another IOM report ( 3 ) , To Err Is Human , focused specifically on the current state of patient safety and ways to improve it . All three of these reports recognized the potential for information technology to be an important agent for change . Computer physician order entry ( CPOE ) allows physicians to enter orders directly into a computer rather than h and writing them ( 46 ) . Because CPOE introduces supportive technology into orderingone of the key processes in medicineit has the potential to address many quality problems . Computer physician order entry affords a health care organization opportunities to st and ardize practice ; incorporate clinical decision support into daily practice ; improve interdepartmental communication ; facilitate patient transfers ; and capture data for management , research , and quality monitoring . It provides physicians and other clinicians with an environment that is more appropriate than a paper-based setting to the complexities of today 's medicine . Patients also can have the comfort of knowing that sophisticated technologies are being applied to help ensure their safety . Because implementing CPOE is an expensive and complex project that touches almost all aspects of the health care operation ( 4 ) , only a few health care organizations in the United States have implemented it ( 4 , 7 , 8) . However , such stakeholders as business , government ( 9 ) , and payers ( 10 ) are creating pressures and incentives for organizations to adopt CPOE . In particular , the Leapfrog Group ( 11 ) , a coalition of the country 's largest employers who are eager to acknowledge and reward health-related quality improvement efforts , has identified CPOE as one of three important leaps that organizations can take to substantially improve patient safety . Many health care organizations are moving forward with CPOE efforts . In 2002 , 67 % of respondents to a survey conducted at the Health Information Management and Systems Society ( HIMSS ) Annual Conference said that their organizations were planning to implement CPOE ; 21 % said that they were currently implementing it , and 29 % said that they were actively discussing it ( 12 ) . As health care organizations decide whether and when to tackle the hurdles of implementing CPOE , they should keep in the forefront of their minds the ways in which this technology can be used to improve health care quality and efficiency . We examine the potential benefits , costs , and other important issues associated with CPOE . Benefits of CPOE The National Roundtable on Health Care Quality ( 1 ) recognized that problems in health care quality fall into three categories : the underuse , overuse , and misuse of health care services . The Roundtable noted that reducing the overuse and misuse of health services leads to an increase in health care quality while decreasing costs . Reducing underuse increases quality but may increase costs .  Computerized physician order entry may affect all three categories of health care quality problems , as well as inefficiencies in the health care system . Table 1 lists studies that have evaluated the effect of CPOE on various aspects of health care . Table 1 . Studies Showing the Effect of Computer Physician Order Entry on Health Care Variables Several studies have shown that CPOE can reduce underuse . Dexter and colleagues ( 13 ) found that , for eligible patients , reminders in CPOE systems increased ordering rates for prophylactic aspirin for coronary artery disease , pneumococcal vaccine , influenza vaccine , and prophylactic subcutaneous heparin . Teich and colleagues ( 14 ) also found an increase in the use of  prophylactic subcutaneous heparin  with CPOE . Overhage and colleagues ( 15 ) demonstrated that compliance with the monitoring of drug levels doubled when automated ordering reminders were implemented . The effect of CPOE on care may depend greatly on the subtle details of the application design . In one evaluation , a decision support feature did not increase compliance with guidelines ( 16 ) ; however , success was realized after the design of the feature was enhanced ( 13 ) . Inappropriate admissions accounted for much of the overuse documented by the IOM report ( 2 ) ; CPOE applications may not be able to affect this problem . However , overuse of diagnostic procedures ( 31 , 32 ) and antibiotics ( 33 ) has been well documented and can be addressed by CPOE . As part of the interaction with the user , CPOE can present cost data ( 17 , 18 ) , previous results ( 19 , 20 ) , and information about the likelihood of finding an abnormal result ( 21 , 34 ) , all of which have been shown to reduce the overuse of diagnostic tests . In one trial , the Centers for Disease Control and Prevention 's guidelines for vancomycin use were embedded in a CPOE application ; 28 % ( P < 0.02 ) fewer patients were prescribed vancomycin or had their  vancomycin order renewed as compared with CPOE without the automated guidelines ( 26 ) . Of two CPOE-based interventions design ed to reduce the use of radiology examinations , one was successful ( 22 ) , while another had minimal impact ( 23 ) . In summary , more study is needed to underst and which quality problems are best suited to remedy by computerized intervention and which system design s are most successful in achieving behavioral change . Misuse of medications is an important concern that leads to various safety problems , including serious medication errors and preventable adverse drug events , as highlighted in the IOM 's recent report ( 3 ) . Two studies that examined the root cause of serious medication errors ( 35 , 36 ) showed that about half were ordering errors such as an incorrect choice of medication for the patient 's condition , an incorrect dose of the medication given the patient 's physiologic state ( for example , renal insufficiency or advanced age ) , and prescribing a medication to which the patient was known to be allergic . Computer physician order entry systems have the potential to address these problems , and studies have shown that CPOE systems can reduce medication errors ( 24 , 25 ) and associated costs and injuries ( 27 ) . The features of CPOE that promote the safe use of medications include patient-specific dosing suggestions ( 14 , 28 , 37 ) , reminders to monitor drug levels ( 15 ) , reminders to choose an appropriate drug ( 14 , 15 , 26 , 27 ) , checking for drugallergy and drugdrug interactions , st and ardized order sets ( that is , departmentally sanctioned predefined collection s of orders that promote safety and efficiency , especially in complex situations ) , increased legibility , automated communication to ancillary departments , and easy access to patient data and reference information while ordering ( 37 ) . A CPOE application with an integrated antibiotic advisor has been shown to reduce the rates of excessive drug dosages and antibiotic-susceptibility mismatches ( 27 ) . Additional medication-related benefits can be realized if CPOE is well integrated with other components of the medication process . The benefits of interfacing CPOE to a pharmacy application have been described ( 38 ) , and interfacing a CPOE application and an electronic medical administration record at one institution eliminated transcription errors ( 29 ) . Although the IOM report ( 3 ) focused on the misuse of medications in the inpatient setting , new data suggest that the magnitude of the problem is similar in the outpatient setting ( 3941 ) . Emerging technologies that automate prescribing and electronically link the ordering provider , the pharmacy , and the patient may address many medication-related problems in the ambulatory environment . Of note , CPOE applications are complex and are intended for use in complex health care environments . Although CPOE has the potential to reduce many sources of error , organizations must take care as CPOE is implemented so that new kinds of errors will not be introduced ( 25 , 42 ) . Most evaluations of CPOE have examined its effect on specific components of the care process , such as the use of diagnostic testing or medication error rates . A few studies have examined the effect of CPOE on overall hospital costs and length of stay . Evans and colleagues ( 27 ) demonstrated reduced costs ( $ 26 325 vs. $ 35 283 ; P < 0.005 ) and length of stay ( 10.0 days vs. 12.9 days ; P < 0.003 ) in patients in an intensive care unit when the suggestions of a computerized antibiotic advisor incorporated into the ordering process were followed . A r and omized , controlled trial at one hospital ( 30 ) indicated that inpatient costs were 12.7 % lower ( P < 0.02 ) and the length of stay was 0.89 day shorter ( P = 0.11 ) for patients on general medicine wards that used  CPOE  with decision support . In a time-series design , Mekhjian and colleagues ( 29 ) documented a decreased length of stay at one of two study hospitals from 3.91 days to 3.71 days ( P = 0.02 ) ; the length of stay at the other hospital in the study did not change , and overall costs at the two study hospitals did not change . Research ers are study ing ways that CPOE can help physicians plan a therapeutic regimen ( 43 , 44 ) . Such planning systems hold special promise for improving quality and safety ; however , they involve complex modeling of diagnosis and therapeutics ( 45 ) . To be successful , planning programs must be integrated tightly into the workflow of the application and must not require excessive additional data entry by the physician . To date , attempts at integrating complex clinical guidelines into CPOE have met with limited success ( 46 , 47 ) , largely because published guidelines , although suitable in printed form for use by practicing clinicians , have been difficult to translate Context Quality -of-care evaluation often focuses on how often patients receive certain tests or treatments . Theoretically , the content of care should predict patient survival , but the evidence is inconclusive . Contribution This study used 207 criteria to assess good care in 372 vulnerable elderly patients . When care did not meet these st and ards , patients were more likely to die during the 3 years of follow-up . Implication s In vulnerable older patients , the content of care is associated with mortality . This finding supports the use of process measures in the evaluation of quality of care and shows that good care may prolong life . The Editors As clinicians , the public , and health systems become more aware that many Americans do not receive necessary care , the importance of measuring and improving quality of care has gained increasing attention ( 1 - 3 ) . Although quality of care can theoretically be measured by outcomes ( what happens to patients ) , process ( what providers do ) is often preferred ( 3 - 5 ) because process is under relatively greater control of providers , needs a shorter time frame , can directly inform improvement , and may not require statistical adjustment for severity of illness ( 6 , 7 ) . Typically , process measures evaluate the proportion of eligible patients who receive care as recommended ( for example , the proportion of patients 65 years of age receiving pneumococcal vaccine ) . To be a meaningful measure of quality , a process of care must be related to improved patient outcomes . For many quality indicators , this relationship is based on evidence of efficacy from r and omized , controlled trials , usually among a select patient population . However , the relationship between performance on  process of care quality indicators  and better health outcomes remains a largely untested assumption for general population s of patients receiving care in community setting s. The lack of a demonstrated relationship between performance on process quality measures and outcome advantage in a cohort of patients has hindered the acceptance of quality indicators as a way to measure and improve health outcomes ( 8) . The Assessing Care of Vulnerable Elders ( ACOVE ) project developed a set of process quality criteria  that were judged by clinical experts to improve patient outcomes on the basis of clinical evidence and professional opinion ( 9 - 11 ) . Combined with mortality information available through the National Death Index , our study evaluated the process outcome relationship . While the development method conferred content validity on the process measures , we aim ed to assess the predictive validity of the quality measurement system by examining the relationship between the quality of care received by sample d participants and their subsequent survival . Methods The ACOVE Project The ACOVE project developed and implemented a set of quality indicators that focuses on process of care for clinical conditions important in the care of vulnerable older patients . Details of the methods of selecting conditions and developing quality indicators have been described in previous reports ( 9 , 10 ) 12 ) . We selected quality indicators by using systematic review s of the medical literature followed by deliberations by several panels of clinical experts using formal consensus methods to assess the validity of quality indicators . This process result ed in 236 quality indicators covering 22 clinical areas ( continuity of care , dementia , depression , diabetes mellitus , end-of-life care , falls and mobility problems , hearing loss , heart failure , hospital care , hypertension , ischemic heart disease , malnutrition , medication management , osteoarthritis , osteoporosis , pain management , pneumonia , pressure ulcer , screening and prevention , stroke and atrial fibrillation , urinary incontinence , and vision care ) across the continuum of care , including prevention , diagnosis , treatment , and follow-up . Each quality indicator contains an if clause that defines the patient who is eligible to receive it and a then clause that describes what care is recommended ( for example : If a vulnerable elder has had a myocardial infa rct ion , then he or she should be offered a -blocker ) . If the medical record describes a contraindication to the recommended care , the patient is not eligible for the quality indicator . Furthermore , we explicitly defined certain indicators as being not applicable , and therefore not included , when assessing the care of patients with advanced dementia or poor prognosis ( 13 ) . We applied the ACOVE quality indicators to a sample of vulnerable older patients in 2 large managed care organizations , 1 in the northeastern United States and the other in the southwestern United States ( 11 ) . Each managed care plan had more than 20000 senior members and contracted with a network of providers for delivery of care . Eligibility criteria included continuous enrollment in the managed care organization with no out-of-network care during the 13-month study period and no active treatment for malignant conditions except for nonmelanoma skin cancer . We identified vulnerable older persons by telephone interview using the Vulnerable Elders Survey-13 ( VES-13 ) ( 14 ) . The VES-13 is a 13-item question naire that produces a vulnerability score ranging from 0 to 10 based on age , self-reported health , and function . Patients with scores of 3 or higher are at 4 times the risk for death or functional decline over the next 2 years and are therefore defined as vulnerable . We excluded nonEnglish- language speakers because interviews were available only in English . Among 3207 community-dwelling patients 65 years of age and older who were r and omly selected from the 2 managed care plans , we conducted screening interviews with 2278 patients ( 9 % through proxies ) and identified 475 ( 21 % ) patients as vulnerable . Among them , 420 ( 88 % ) patients consented to participate in the study and 372 ( 78 % ) patients had medical records for the 13-month period from 1 July 1998 to 31 July 1999 that were able to be abstract ed . We collected all participants ' medical records , including those for inpatient care , outpatient care , nursing home care , home care , and mental health care . Trained nurses abstract ed charts to apply quality indicators . A senior nurse review er assessed completed abstract ions , and physician overreaders review ed them for clinical assessment . We evaluated inter-rater reliability by re abstract ion of 10 % of the medical records , which contained 698 quality indicators . Agreement was 97 % for quality indicator eligibility and 95 % for overall quality score . We collected patient characteristics , including age , sex , cognitive function measured by the Blessed OrientationMemoryConcentration test ( 15 ) , and mental health score derived from Medical Outcomes Study Short Form-36 items ( 16 ) , at the time of the recruitment telephone interview . The R AND institutional review board approved the study protocol . Among the 236 ACOVE quality indicators , 207 could be implemented in the field trial either by medical record  ( 183 indicators ) or patient interview  ( 24 indicators ) . Because some patients died before the interview was conducted , we used only quality indicators for which information was available in medical records . Among these , 160 quality indicators had at least 1 eligible patient ; 43 focused on prevention , 42 on diagnosis , 47 on treatment , and 28 on follow-up care . These 160 quality indicators covered all 22 conditions . The Appendix Table contains the list of quality indicators used in our report , the number of eligible patients , and the pass rate for each indicator . Appendix Table . Quality Indicators Using Medical Records as the Information Source , Eligible Patients , and Pass Rates Statistical Analysis We calculated quality scores for each patient on the basis of the percentage of ACOVE quality indicators for which an eligible patient received recommended care . We obtained death , date , and cause-of-death data for ACOVE participants from the National Death Index during 3 years after the quality measurement period ( from August 1999 to September 2002 ) . We used both unadjusted and adjusted analyses to examine the link between patient survival and quality score . For the unadjusted analysis , we first divided the sample in half on the basis of quality score ( that is , median and < median ) and examined the difference in survival curves between patients with higher quality and patients with lower quality by using the log-rank test . Second , we calculated survival for 10 equal intervals of quality score from the lowest quality score to the highest quality score in the sample and graphically assessed the grade d relationship between quality score and survival . We used the Cox proportional hazards survival model in adjusted analyses . Because the proportional hazards assumption for the multivariate survival analysis did not hold for the entire observation period , we used a piecewise model that allowed the coefficients for quality to vary between 500 days or less and more than 500 days , as suggested by the KaplanMeier survival curve in the unadjusted analysis . Covariates included sex , VES-13 score ( including age ) , mental health , number of hospitalizations and office visits during the quality measurement period , and number of conditions that patients had during the quality measurement period among 13 comorbid conditions ( dementia , depression , diabetes mellitus , heart failure , hypertension , ischemic heart disease , osteoarthritis , osteoporosis , pressure ulcer , atrial fibrillation , urinary incontinence , chronic obstructive pulmonary disease , and chronic renal failure ) . The mental health score ranged from 1 to 6 , and we created 3 categories on the basis of the score ( < 2 , very good ; 2 to 3 , good ; and > 3 , fair ) . An indicator variable design ated patients who were not interviewed for mental health items because of cognitive impairment . To further examine a plausible mechanism for the quality survival link , we examined the relationship between survival and ABSTRACT BACKGROUND Patients at risk for generating high health care expenditures often receive fragmented , low- quality , inefficient health care . Guided Care is design ed to provide proactive , coordinated , comprehensive care for such patients . OBJECTIVE We hypothesized that Guided Care , compared to usual care , produces better functional health and quality of care , while reducing the use of expensive health services . DESIGN 32-month , single-blind , matched-pair , cluster-r and omized controlled trial of Guided Care , conducted in eight community-based primary care practice s. PATIENTS The “ Hierarchical Condition Category ” ( HCC ) predictive model was used to identify high-risk older patients who were insured by fee-for-service Medicare , a Medicare Advantage plan or Tricare . Patients with HCC scores in the highest quartile ( at risk for generating high health care expenditures during the coming year ) were eligible to participate . INTERVENTIONA registered nurse collaborated with two to five primary care physicians in providing eight services to participants : comprehensive assessment , evidence -based care planning , proactive monitoring , care coordination , transitional care , coaching for self-management , caregiver support , and access to community-based services . MAIN MEASURES Functional health was measured using the Short Form–36 . Quality of care and health services utilization were measured using the Patient Assessment of Chronic Illness Care and health insurance cl aims , respectively . KEY RESULTS Of the eligible patients , 904 ( 37.8 % ) gave written consent to participate ; of these , 477 ( 52.8 % ) completed the final interview , and 848 ( 93.8 % ) provided complete cl aims data . In intention-to-treat analyses , Guided Care did not significantly improve participants ’ functional health , but it was associated with significantly higher participant ratings of the quality of care ( difference = 0.27 , 95 % CI = 0.08–0.45 ) and 29 % lower use of home care ( 95 % CI = 3–48 % ) . CONCLUSIONS Guided Care improves  high-risk older patients ’ ratings of the quality of their care , and it reduces their use of home care , but it does not appear to improve their functional health IMPORTANCE Most evaluations of pay-for-performance ( P4P ) incentives have focused on large-group practice s. Thus , the effect of P4P in small practice s , where many US residents receive care , is largely unknown . Furthermore , whether electronic health records ( EHRs ) with chronic disease management capabilities support small- practice response to P4P has not been studied . OBJECTIVE To assess the effect of P4P incentives on quality in EHR-enabled small practice s in the context of an established quality improvement initiative . DESIGN , SETTING , AND PARTICIPANTS A cluster-r and omized trial of small ( < 10 clinicians ) primary care clinics in New York City from April 2009 through March 2010 . A city program provided all participating clinics with the same EHR software with decision support and patient registry functionalities and quality improvement specialists offering technical assistance . INTERVENTIONS Incentivized clinics were paid for each patient whose care met the performance criteria , but they received higher payments for patients with comorbidities , who had Medicaid insurance , or who were uninsured ( maximum payments : $ 200/patient ; $ 100,000/clinic ) . Quality reports were given quarterly to both the intervention and control groups . MAIN OUTCOMES AND MEASURES Comparison of differences in performance improvement , from the beginning to the end of the study , between  control  and  intervention  clinics for  aspirin or antithrombotic prescription , blood pressure control , cholesterol control , and smoking cessation interventions .  Mixed-effects logistic regression was used to account for clustering of patients within clinics , with a treatment by time interaction term assessing the statistical significance of the effect of the intervention . RESULTS Participating clinics ( n = 42 for each group ) had similar baseline characteristics , with a mean of 4592 ( median , 2500 ) patients at the intervention group clinics and 3042 ( median , 2000 ) at the control group clinics . Intervention clinics had greater adjusted absolute improvement in rates of appropriate antithrombotic prescription ( 12.0 % vs 6.1 % , difference : 6.0 % [ 95 % CI , 2.2 % to 9.7 % ] , P = .001 for interaction term ) , blood pressure control ( no comorbidities : 9.7 % vs 4.3 % , difference : 5.5 % [ 95 % CI , 1.6 % to 9.3 % ] , P = .01 for interaction term ; with diabetes mellitus : 9.0 % vs 1.2 % , difference : 7.8 % [ 95 % CI , 3.2 % to 12.4 % ] , P = .007 for interaction term ; with diabetes mellitus or ischemic vascular disease : 9.5 % vs 1.7 % , difference : 7.8 % [ 95 % CI , 3.0 % to 12.6 % ] , P = .01 for interaction term ) , and in smoking cessation interventions  ( 12.4 % vs 7.7 % , difference : 4.7 % [ 95 % CI , -0.3 % to 9.6 % ] , P = .02 for interaction term ) . Intervention clinics performed better on all measures for Medicaid and uninsured patients except cholesterol control , but no differences were statistically significant . CONCLUSIONS AND RELEVANCE Among small EHR-enabled clinics , a P4P incentive program compared with usual care result ed in modest improvements in cardiovascular care processes and outcomes . Because most proposed P4P programs are intended to remain in place more than a year , further research is needed to determine whether this effect increases or decreases over time . TRIAL REGISTRATION clinical trials.gov Identifier : NCT00884013 PURPOSE Major primary care reforms have been introduced in recent years in the United Kingdom , including financial incentives to improve clinical quality and provide more rapid access to care . Little is known about the impact of these changes on patient experience . We examine patient reports of quality of care between 2003 and 2007 , including r and om sample s of patients on practice lists and patients with long-term conditions . METHODS We conducted a cross-sectional design study of family practice s in which  question naires were sent to serial sample s of patients in 42 representative general practice s in Engl and . Question naires sent to sample s of patients with chronic disease ( asthma , angina , and diabetes ) and r and om sample s of adult patients ( excluding patients who reported any long-term condition ) in 2003 , 2005 , and 2007 addressed issues of access , communication , continuity of care , coordination , nursing care , and overall satisfaction . RESULTS There were no significant changes in quality of care reported by either group of patients between 2003 and 2007 for communication , nursing care , coordination , and overall satisfaction . Some aspects of access improved significantly for patients with chronic disease , but not for the r and om sample s of patients . Patients in both sample s reported seeing their usual physician less often and gave lower satisfaction ratings for continuity of care . Most scores were significantly higher for the chronic illness sample s than for the r and om sample s of patients in 2003 , even after adjusting for age . CONCLUSIONS There was a modest improvement in access to care for patients with chronic illness , but all patients now find it somewhat harder to obtain continuity of care . This outcome may be related to the incentives to provide rapid appointments or to the increased number of specialized clinics in primary care . The possibility of unintended effects needs to be considered when introducing pay for performance schemes The national health care debate reflects the fervent and sometimes disparate views that patients and physicians have on what is important in health care . Research has found that patient satisfaction is clearly composed of many elements . Such diverse issues as technical skill , communication , accessibility , physical qualities of the facility , and coordination of care all seem to play a role in satisfying patients [ 1 - 4 ] . However , few research ers have attempted to determine the priorities that patients assign to attributes of care . In the early 1980s , Fletcher and colleagues [ 5 ] studied the priorities of 225 patients attending an academic medical clinic and found that continuity of care was the highest priority for these patients and that issues of cost and convenience were lowest . Robbins and colleagues [ 6 ] studied 100 patient visits to an academic primary care practice and found that overall satisfaction with the visit appeared to be related to aspects of the physical examination , time spent on health education , and discussion of the effects of treatment . We know of no published attempts to establish patient priorities in nonacademic setting s , and no empirical comparisons of patients ' and physicians ' opinions on the importance of various elements of health care are readily available . Thus , we surveyed patients and physicians for their opinions on the importance of various specific attributes of care to the overall quality of outpatient care . Methods Study Sample s Physicians Governors of the American College of Physicians from Arizona , Michigan , Oklahoma , Tennessee , Georgia , Maine , and Connecticut helped recruit a total of 74 members of the College from their respective states . These states were selected because they represented a wide geographic area . Only physicians who spent at least 60 % of their time practicing general internal medicine were eligible to participate . Full-time academicians , full-time specialists , full-time research ers , and trainees were excluded . The seven College governors each provided the names of 10 to 15 physicians from their own states who met these eligibility criteria and were thought to be exemplary clinicians . Research personnel sent these physicians ( n = 81 ) a letter explaining that the College governor had recommended them for participation in this project . Telephone follow-up was used to describe the project in detail . Of the 81 physicians recruited , 74 ( 91 % ) agreed to participate ; these 74 physicians make up our physician sample . Patients After participating physicians notified the patients they saw during a specified 2-week period that the patients might be contacted to participate in a voluntary , confidential study of quality of care , the physicians gave study personnel copies of their appointment logs for this period . Research staff r and omly selected 11 patients listed in each office 's log to participate in the study ( n = 814 ) according to the following procedure , which was devised by the firm that administered the surveys . Research staff divided the total number of patients listed on the log by 11 ( the target sample size for each practice ) to obtain a number , A. They rounded A up to the next highest integer and went to the Ath number on the r and om-number table . That r and om number was divided by 10 to obtain a number , B. The number B was rounded to the next highest integer , and the Bth patient on the log became the first patient in the sample . The second patient was selected by adding A and B to get a number , C. The Cth number on the r and om-number table was then divided by 10 and rounded to the next highest integer to obtain a number , D. The Dth patient listed on the physician 's log became the second patient in the sample . The third patient was selected by adding A and D and repeating the same process . The physicians and their staffs had no role in selecting patients from the logs and were not aware of subsequent patient participation . Question naire Using the literature on patient perceptions of care and separate focus groups with patients and physicians , we identified a comprehensive list of elements of medical office practice thought to be associated with quality of care in that setting . The 125 elements thought to be important in the delivery of high- quality office-based care covered the following nine domains , which were defined a priori : physician clinical skill , physician interpersonal skill , office support staff , office environment , provision of health-related information , patient involvement in care , nonfinancial access , finances , and coordination of care . The domains are defined in Table 3 . In this report , we refer to the 125 elements of care as elements , attributes , or items . Table 3 . Appendix : Definition of Domains We then constructed a question naire that asked both physician and patient respondents to rate , from their own perspectives , the importance of each of the 125 elements to the quality of care delivered in a physician 's office ( Table 4 ) . Respondents rated each item using a 4-point scale : 1 signified that the respondent considered the item not important ; 2 indicated that the item was of medium importance ; 3 meant that the item was of high importance ; and 4 indicated that the item was essential . Patients and physicians were asked to rate the importance of each item to office-based care in general , not to the performance of the patient 's individual physician or to the physician 's own practice . Table 4 . Appendix : Summary of Question naire : Instructions , Domains , and Sample Items Data Collection and Analysis An independent survey firm mailed the  question naire to participants within 1 month of the index visit . Data collection remained open for 5 weeks , and reminders were sent 1 week after the initial mailing . We used group consensus to cluster items into the domains on the basis of qualitative assessment . When agreement about which domain an item belonged to was not unanimous , we discussed the item as a group until we reached a consensus . During a separate phase of our research that examined patients ' reports on the performance of their physicians , we also did a factor analysis that loosely guided the assignment of items to domains . The factor analysis identified two factors . The first was related to the specific skills and style of the physician and thus encompassed the domains of physician clinical skill , physician interpersonal skill , provision of health-related information , and patient involvement in care . The second factor was less directly related to physician skill or style and was thought to encompass the domains of office support staff , office environment , nonfinancial access , coordination of care , and finances . The assignment of items to the nine domains was guided by whether the item belonged to a domain related to the first factor or to the second factor . We examined the median importance ratings and interquartile ranges of physicians ' and patients ' ratings for each element of care and then analyzed items aggregated into the nine domains . For each respondent , we determined a domain-specific importance rating by calculating the average rating that the respondent assigned to items in each of the nine domains that the question naire addressed . For example , if a respondent assigned importance ratings of 2 , 3 , 3 , 3 , 4 , and 4 to the six items in the domain of office environment , that person 's rating of the importance of the office environment domain would be 3.17 ( [ 2 + 3 + 3 + 3 + 4 + 4]/6 ) . We then determined the median importance ratings assigned to each domain by the patients and by the physicians and used the Mann-Whitney U test to compare the two groups . We also ranked the perceived importance of the domains for patients and physicians by ordering the domains from those with the highest importance score to those with the lowest . We then compared the rank orders of physicians ' and patients ' ratings of the nine domains using the Spearman rank-order correlation coefficient . All reported P values are two sided . Results Physician and Patient Characteristics All 74 physicians who supplied appointment logs were in solo or small-group practice . The mean age was 44 years , 14.9 % were women , and 8 % belonged to an ethnic minority group . Nine physicians were from Arizona , 9 were from Michigan , 15 were from Oklahoma , 11 were from Tennessee , 12 were from Georgia , 9 were from Maine , and 9 were from Connecticut . Of the 74 physicians , 69 ( 93 % ) completed the study question naire . Of these 69 physicians , the mean age was 45.5 years , 16 ( 22 % ) were women , 5 ( 7 % ) belonged to an ethnic minority group , and all were in solo or small-group practice . The patient response rate was 60 % ( 485 of 815 patients ) . The characteristics of these patients are shown in Table 1 . Table 1 . Patient Characteristics Patients ' and Physicians ' Ratings of the Importance of Individual Elements Physicians and patients differed substantially in an element-by-element comparison of ratings . Disagreement about the level of importance was statistically significant for 58 % of the elements ( 72 of 125 ) . Table 2 shows data for the 15 elements on which patients ' and physicians ' ratings greatly differed . Of note , 9 of the 15 largest differences concerned the provision of information to the patient . Table 2 . Elements of Care for Which Patients ' and Physicians ' Importance Ratings Differed Most Patients ' and Physicians ' Ratings of the Importance of the Domains Patients and physicians agreed strongly about the rank order of the nine domains ( Spearman r , 0.80 ) . For example , both groups ranked clinical skills highest and office environment lowest . Provision of information was the only domain for which the rank order substantially differed between groups . Physicians ranked office support staff , physician interpersonal skill , patient involvement , and coordination of care higher than patients did , but these differences were not statistically significant . Although agreement on rank order ( that is , relative importance ) was Scientific background Poor compliance or adherence in  drug therapy  can cause increased morbidity , mortality and enormous costs in the healthcare system ( in Germany annually approximately 10 billion euros ) . Different methods are used for enhancing the compliance or adherence . Research questions The evaluation addresses the questions about existence , efficacy , cost-benefit relation as well as ethical-social and juridical implication s of strategies for enhancing compliance or adherence in drug therapy with concomitant improvements in treatment outcomes . Methods A systematic literature search was conducted in the medical , also health economic relevant , literature data bases in January 2007 , beginning from 2002 . Systematic review s on the basis of ( r and omised controlled trials ( RCT ) concerning interventions to enhance compliance or adherence with regard to treatment outcomes as well as systematic review s of health economic analyses were included in the evaluation . Additionally , it was also search ed for publications which primarily considered ethical-social and juridical aspects of these interventions for the German context . Results One systematic review with data for 57 RCT was included in the medical evaluation and one systematic review with data for six studies into the health economic evaluation . No publication primary concerning ethical-social or juridical implication s could be identified . A significant positive effect on the treatment outcome was reported for 22 evaluated interventions . For many interventions the results can be classified as reliable : counseling with providing an information leaflet and compliance diary chart followed by phone consultation for helicobacter pylori positive patients , repeated counseling for patients with acute asthma symptoms , telephone calls to establish the level of compliance and to make recommendations based on that for the therapy of cardiovascular diseases , calls of an automated telephone system with phone counseling in problem cases for diabetics , different family based interventions including repeated family counseling , education and " culturally modified family therapy " in patients with schizophrenia , repeated " compliance therapy " sessions for patients with acute psychosis . For other interventions the results should be viewed with more concern ( because of the poor method ical quality of the underlying studies ) . The effect size of the interventions can not be estimated from the available data . From the available data , no reliable results can be provided concerning the cost-benefit relation of these strategies . Discussion Many of the reported studies had a poor reporting and method ological quality . The reliability of the conclusions of the studies is restricted because of method ical shortcomings . Efficacy and cost estimates determined in the health economic studies are not transferable to the current situation in Germany . It has been discussed recently that the compliance or adherence enhancing interventions can restrict the autonomy and the privacy of the patients . Conclusions In drug therapy some compliance or adherence enhancing interventions with concomitant positive effect on the treatment outcome may be used . The cost-benefit relation of these interventions is to be estimated . Using these interventions the patient ’s autonomy and privacy are to be restricted as few as possible Objective . Immunizations and other cost-effective preventive services remain underused by many children , especially those living in poverty . Given the effectiveness of provider-based tracking systems and the widespread use by managed care organizations of financial incentives to influence physician practice patterns , we design ed and tested an intervention combining these strategies . We studied whether a system of semiannual assessment and feedback , coupled with financial incentives , could improve pediatric preventive care in a Medicaid health maintenance organization ( HMO ) . Methodology . We r and omly assigned primary care sites serving children in a Medicaid HMO to one of three groups : a feedback group ( where physicians received written feedback about compliance scores ) , a feedback and incentive group ( where physicians received feedback and a financial bonus when compliance criteria were met ) , and a control group . We evaluated compliance with pediatric preventive care guidelines  through semiannual chart audits during the years 1993 to 1995 . Results . Compliance with pediatric preventive care improved dramatically in the study period . Repeated measures ANOVA demonstrated a significant increase in all three study groups throughout the time in total compliance scores ( from 56%–73 % ) , as well as scores for immunizations ( from 62%–79 % ) and other preventive care ( from 54%–71 % ) . However , no significant differences were observed between either intervention group and the control group , nor were there any interaction ( group-by-time ) effects . Conclusions . Feedback to physicians , with or without financial incentives , did not improve pediatric preventive care in this Medicaid HMO during a time of rapid , secular improvements in care . Possible explanations include the context and timing of the intervention , the magnitude of the financial incentives , and lack of physician awareness of the intervention Context Multi-institutional quality improvement collaboratives are popular , but are they effective ? Contribution This controlled study evaluated an HIV care Breakthrough Series program that emphasized provider teams , sessions on quality improvement theory and techniques , and report backs about implementing quality improvement . A review of the medical records of 9986 HIV-infected patients showed no important differences in  quality of care ( viral load suppression , pneumocystitis prophylaxis , and screening for tuberculosis and hepatitis ) between the 44 intervention clinics and the 25 control clinics . Caution s Patient adherence and satisfaction were not measured , and some control clinics may have used quality improvement techniques similar to those recommended by the collaborative program . The Editors In the pastdecade , tremendous improvements have occurred in measuring and monitoring the quality of medical care in the United States . Despite these advances , striking problems with quality persist ( 1 , 2 ) . The quality of care for patients with HIV infection is of particular concern . Substantial evidence shows that obtaining medical services and treatment for patients with HIV infection may lead to longer survival and better quality of life ( 3 , 4 ) , yet serious quality -of-care problems and striking disparities in quality by race and social class have been documented ( 4 - 6 ) . In the 1980s , continuous quality improvement techniques were introduced into health care ( 7 , 8) . These strategies emphasize that most quality problems are a result of system failings rather than problems with individual practitioners ( 9 ) . In 1995 , the Institute for Healthcare Improvement introduced the concept of the Breakthrough Series , which brings together health care organizations dedicated to improving the quality of care in particular clinical areas through the application of continuous quality improvement techniques ( 10 ) . These techniques ( known as Plan/Do/ Study /Act or PDSA cycles ; Figure 1 ) first identify deficiencies in quality , next repeatedly implement small-scale interventions and measure changes , and then refine and exp and interventions to improve processes of care ( 11 , 12 ) . Typically , each Breakthrough Series collaborative is composed of 20 to 40 participating health care organizations and a faculty with expertise in the clinical area and quality improvement methods ( 13 ) . To date , the Institute for Healthcare Improvement has conducted collaboratives with more than 700 teams working on 23 clinical conditions or treatment processes , including improving asthma care and reducing medication errors . Although some evaluations of quality before and after a collaborative support the validity of this approach , only a few limited controlled trials have been conducted ( 14 , 15 ) . Figure 1 . Theoretical construct of continuous quality improvement . An important source of funding for HIV care is the Ryan White Comprehensive AIDS Re sources Emergency ( CARE ) Act , which is administered by the HIV/AIDS Bureau of the Health Re sources and Services Administration . Title III of the CARE Act supports comprehensive primary health care for HIV-infected individuals and currently supports primary care services for more than 150000 patients receiving care in more than 200 community health centers , hospital-based clinics , and city or county health services ( 16 ) . In 1999 , the Health Re sources and Services Administration required all clinical sites that were newly awarded funding under Title III of the CARE Act to participate in a quality improvement collaborative conducted by the Institute for Healthcare Improvement . Other sites already receiving Title III funding were also invited to participate . This study evaluates the impact of the collaborative by examining pre- and postimplementation quality -of-care information on sample s of patients from both participating and matched nonparticipating clinics . Methods Study Site Selection and Controls Of the 200 Title III sites in the continental United States in May 2000 , we excluded 16 that reported caseloads of fewer than 100 cases per year , 12 that were initially slated to participate in the Breakthrough collaborative but elected not to do so , and 1 that lost its CARE Act funding shortly before the collaborative began . Of the remaining 171 sites , 62 participated in the collaborative . Among these sites , 54 agreed to participate in the study and 44 ( including 11 m and atory participants and 33 voluntary participants ; 71 % of collaborative participants ) provided chart review data . Of the 109 nonparticipating sites eligible to be selected as control sites , 65 provided information needed for matching . The potential control sites were matched with intervention sites on the basis of the type of site ( community health center , community-based organization , health department , hospital , or university medical center ) , location ( rural or urban ) , number of locations delivering care , region , and number of patients with active HIV infection . When these criteria were used , 40 sites were selected as potential controls and 37 of them ( 93 % ) agreed to participate in the study . Of these , 25 ( 63 % of potential control sites ) participated in the chart review portion of the study . The Committee on Human Studies of Harvard Medical School approved the study protocol . Quality Improvement Intervention Each participating clinic selected a team , usually consisting of at least one administrator and one or more clinicians , and a population of focus on which the team 's interventions would be tested . Usually , the population of focus consisted of all HIV-infected patients in a particular site , but participants sometimes chose to focus on a subset of patients , such as those under the care of a particular group of clinicians . Originally , the design of the collaborative extended for 12 months and included a kickoff meeting and 2 subsequent 2-day meetings called learning sessions . The kickoff learning session included instruction in the theory and practice of quality improvement by identifying problems in HIV care and then introducing the techniques of continuously implementing , measuring , and refining changes ( the Plan/Do/ Study /Act cycles ) ( 11 , 12 ) to improve the care of HIV-infected patients . Each learning session included additional instruction in quality improvement techniques and breakout sessions that focused on improving specific aspects of care , developing an information infrastructure to track progress , and specific aspects of quality improvement theory . In addition , teams exchanged ideas and presented storyboards of their progress to date . At each session , teams reported on activities , methods , and results . Toward the end of the 12-month period , the Health Re sources and Services Administration decided to extend the collaborative by 4 months and add a third learning session . Between the sessions ( action periods ) , team members implemented concepts and ideas . Each site had access to a collaborative listserve , participated in monthly conference calls with the collaborative faculty , and su bmi tted monthly reports of its improvements , which included charts that tracked the site 's improvements to date in the required key quality measures described in the next section . Detailed descriptions of the Breakthrough Series collaboratives are available elsewhere ( 10 , 17 - 19 ) . Quality -of-Care Monitors We selected quality -of-care measures ( Table 1 ) to coincide with required and optional quality measures selected by the collaborative faculty as areas for improvement . These measures were selected by the faculty after review ing the literature to identify areas of quality deficiency in the delivery of HIV care , particularly for underserved population s targeted by the CARE Act . Because of the paramount importance of antiretroviral therapy to the treatment of HIV infection , the faculty focused on measures related to antiretroviral treatment , including the percentage of patients receiving highly active antiretroviral therapy , the percentage of patients with a controlled viral load , and the percentage of patients who received adherence counseling , as required key measures for the collaborative . Measures were then developed on the basis of consensus guidelines appropriate for the period of care ( 20 ) . Our primary measures were rates of highly active antiretroviral therapy use and control of HIV viral load for appropriate patients . Patients eligible for highly active antiretroviral therapy included those with CD4+cell counts less than 0.350 109 cells/L , those with CD4+counts between 0.350 and 0.500 109 cells/L and a viral load greater than 5000 copies/mL , all patients with a viral load greater than 30000 copies/mL , and patients already receiving highly active antiretroviral therapy , as per the guidelines . We also assessed the use of  highly active antiretroviral therapy for those with CD4+counts less than 0.350 109 cells/L to reflect recommendations that were published after the end of the collaborative ( 21 ) . Because of the variability in viral load assays available at the time , viral load was considered controlled if it was undetectable or if the total viral load was less than 400 copies/mL. We also assessed the  use of screening and prophylaxis  , as well as  access to care .  The only key measure followed by the collaborative that we could not assess was related to adherence counseling because this information is not reliably available from medical records . Table 1 . Quality of Care Indicators * Quality -of-Care Data Collection To identify pre- and postintervention sample s of patients , we requested lists of all HIV-infected patients in care at each of the sites during the 2 time periods ( Figure 2 ) . For the first sample , sites were asked to provide encrypted lists of all HIV-infected patients age 18 years or older as of June 2000 seen at the site between 1 January and 30 June 2000 . For the second sample , sites were asked to provide a similar list of active patients age 18 years or older as of OBJECTIVE To evaluate how a primary care reform , which aim ed to promote interprofessional and interorganizational collaborative practice s , affected patients ' experiences of the core dimensions of primary care . DESIGN Before- and -after comparison of patients ' perceptions of care at the beginning of  family medicine group ( FMG ) implementation  ( 15 to 20 months after accreditation ) and 18 months later . SETTING  Five FMGs in the province of Quebec from various setting s and types of practice . PARTICIPANTS A r and om sample of patients was selected in each FMG ; a total of 1046 participants completed both the baseline and follow-up question naires . MAIN OUTCOME MEASURES Patients ' perceptions of relational and informational continuity , organizational and first-contact accessibility , attitude and efficiency of the clinic 's personnel and waiting times ( service responsiveness ) , physician-nurse and primary care physician-specialist coordination , and intra-FMG collaboration were assessed over the telephone , mostly using a modified version of the  Primary Care Assessment Tool . Additional items covered patients ' opinions about consulting nurses , patients ' use of emergency services , and patients ' recall of health promotion and preventive care received . RESULTS A total of 1275 patients were interviewed at the study baseline , and 82 % also completed the follow-up interviews after 18 months ( n = 1046 ) . Overall , perceptions of relational and informational continuity increased significantly ( P < .05 ) , whereas organizational and first-contact accessibility and service responsiveness did not change significantly . Perception of physician-nurse coordination remained unchanged , but perception of primary care physician-specialist coordination decreased significantly ( P < .05 ) . The proportion of participants reporting visits with nurses and reporting use of FMGs ' emergency services increased significantly from baseline to follow-up ( P < .05 ) . CONCLUSION This reorganization of primary care services result ed in considerable changes in care practice s , which led to improvements in patients ' experiences of the continuity of care but not to improvements in their experiences of the accessibility of care Background The UK 's Quality and Outcomes Framework ( QOF ) was introduced in 2004/5 , linking remuneration for general practice s to recorded quality of care for chronic conditions , including diabetes mellitus . We assessed the effect of the incentives on recorded quality of care for diabetes patients and its variation by patient and practice characteristics . Methods Using the General Practice Research Data base we selected a stratified sample of 148 English general practice s in Engl and , contributing data from 2000/1 to 2006/7 , and obtained a r and om sample of 653 500 patients in which 23 920 diabetes patients identified . We quantified annually recorded quality of care at the patient-level , as measured by the 17  QOF diabetes indicators , in a composite score and analysed it longitudinally using an Interrupted Time Series design . Results Recorded quality of care improved for all subgroups in the pre-incentive period . In the first year of the incentives , composite quality improved over- and -above this pre-incentive trend by 14.2 % ( 13.7–14.6 % ) . By the third year the improvement above trend was smaller , but still statistically significant , at 7.3 % ( 6.7–8.0 % ) . After 3 years of the incentives , recorded levels of care varied significantly for patient gender , age , years of previous care , number of co-morbid conditions and practice diabetes prevalence . Conclusions The introduction of financial incentives was associated with improvements in the recorded quality of diabetes care in the first year . These improvements included some measures of disease control , but most captured only documentation of recommended aspects of clinical assessment , not patient management or outcomes of care . Improvements in subsequent years were more modest . Variation in care between population groups diminished under the incentives , but remained substantial in some cases
The intervention sites admitted statistically significantly more severely ill patients  than nursing homes in the control group .
Despite the
In the report Crossing the Quality Chasm ( 1 ) , the Institute of Medicine called attention to the poor quality of health care in the United States .
The Institute identified numerous factors contributing to poor quality , including the structure of the present health care payment system .
The Institute found that , for certain clinical situations , health care payment arrangements may actually produce disincentives for quality .
The largely untapped potential of the health care payment system to change physician and health care system behavior has stimulated interest in both the scientific literature ( 2 , 3 ) and the popular press ( 4 - 6 ) for linking payments to performance on quality measures .
Several health plans ( 3 , 7 ) and the Centers for Medicare & Medicaid Services are using explicit financial incentives for quality ( 8 , 9 ) .
For example , what types of clinical conditions or health care services should be the target of financial incentives to improve quality : chronic diseases , acute care , or preventive care services ?
How effective ( and cost-effective ) are financial incentives for quality ?
What are the optimum magnitude , frequency , and duration of financial incentives for quality ?
What is the optimum package of nonfinancial interventions ( if any ) to include with financial incentives for quality , for example , audit and feedback , recognition , clinical reminders , academic detailing , or information technology support ( 12 , 13 ) ?
Can we expect the effect of financial incentives to persist after they are stopped ?
Because any effective intervention will have some unanticipated effects , will important patient care activities that are not rewarded financially be neglected ?
The purpose of this paper is to assess the relationship between explicit financial incentives and the provision of high- quality health care by systematic ally review ing empirical studies .
Because the evidence regarding the relationship between the financial incentives embedded in fee-for-service and capitation arrangements and the quality of health care has been thoroughly review ed in previous work ( 14 ) , we focused our review on literature that addresses explicit financial rewards for improving health care quality .
Methods Study Identification and Selection We conducted a systematic search of the English- language literature in PubMed to find articles published between 1 January 1980 and 14 November 2005 whose main objective was to assess the use of explicit financial incentives to improve health care quality .
Access to care is the patient 's attainment of timely and appropriate health care .
Structure of care is a feature of a health care organization or clinician relevant to the provision of health care .
Process of care is a health care service provided to or on behalf of a patient .
Outcome of care is a health state of a patient result ing from health care .
Concurrent comparison groups are important because some studies of quality may show dramatic improvement over time but no statistically significant differences between intervention and comparison groups .