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Abstract Comparative cross-case analysis of service models for patients with chronic kidney conditions in Klong Klung and Kong Rha Districts, Thailand

Paibul Suriyawongpaisal*, Samrit Srithamrongsawat*, Vinai Leesmidt^†, Kadethip Buakaew^‡, Suda Khumnurak^§, Kavin Klubkun^§

*Department of Community Medicine, Faculty of Medicine Ramathibodi Hospital, Mahidol University

†Klong Klung Hospital, Kamphaeng Phet Province, ^‡Phatthalung Hospital, Phatthalung Province

§Kong Rha Hospital, Phatthalung Province

The expansion of benefit package covering patients with chronic kidney diseases (CKD) since 2007 resulted in increased access to care and minimized disparity of access to renal replacement therapy (RRT) across public health insurance schemes. Nonetheless, growing concerns of financial burden to the public health programs ensued. This poses a challenge for policy makers in terms of inventing preventive or mitigation measures for CKD.

Recently (2016) Ministry of Public Health promulgated upscaling of Klong Klung Model (KKM) as a prototype for such measures after the findings of effectiveness of the model. Given complexity of the health care systems, the upscaling might not be straightforward. There is still need for clarification of what and how building blocks of the model were developed under specific circumstance of Klong Klung District in Khampang Phet Province, a lower northern province.

Using comparative cross-case analysis, this report gathered data from focus-group discussions, direct observation and documentary review relevant to development of CKD care models in Klong Klung District and its comparator in Kong Rha District, Phattalung Province in the South.

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It was found that KKM, with a focus on prevention and mitigation of CKD, was developed based on randomized controlled trial to test a standardized protocol jointly determined by Klong Klung Hospital and the Kidney Disease Institute of Thailand. To the contrary, the care model at Kong Rha District covered a spectrum of care ranging from prevention to RRT. Kong Rha adopted a trial and error approach in applying existing knowledge acquired by the local team in close collaboration with a multidisciplinary team of Phattalung Hospital (the referral center of the province) led by an internist with training in kidney dialysis. Given such differences, both models shared a common feature of leadership: sustained leading role of a senior nurse head for Kong Rha and of the hospital director for Klong Klung. Both leaders was found to perform in a remarkably autonomous status based on patient-centric principle. Under this lead- ership style, multidisciplinary team members interacted on an equal ground rendering ongoing learning and adaptation.

In term of generating knowledge on the effectiveness, KKM was found to be much more systematic in data management and analysis reflecting a significant technical contribution from academic experts of the institute. In contrast, Kong Rha faced with limited capacity in terms of manpower and technical expertise in making use of the data. This resulted as expected in more ambiguous findings to prove the effectiveness of the model. In effect, the limitations of Kong Rha reflect widespread phenomenon of slug- gish development of the capacity to make use of existing health information systems in the country de- spite substantial investment in the hardware.

Finally, we did not find “vulnerable population” as a common language among the study areas. This does not mean that the health professionals play down the importance of ensuring access to care of the poor or the disadvantaged. To the opposite, they have made substantial attempts to do so. For instance, community resources were mobilized to reconstruct a sufficient hygienic space for home-based peritoneal dialysis in Kong Rha. Under KKM frequent home visits to all the patients especially the poor enabled better understanding of limited food choices contributing to difficulty in sodium reduction. This led to modification of dietary education to be more suitable to the poor patients’ situation.

Keywords: comparative cross-case analysis, CKD, RRT, NCD, model, prevention

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√–‡∫’¬∫«‘∏’»÷°…“

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Health Systems Building Blocks⁽¹⁵⁾ ´÷Ëß¡ÿàßÕ∏‘∫“¬§«“¡

 —¡æ—π∏å√–À«à“ß°“√®—¥∫√‘°“√ ÿ¢¿“æ √–∫∫ π—∫ πÿπ (°“√

‡ß‘π°“√§≈—ß ∑√—欓°√∫ÿ§§≈ °“√Õ¿‘∫“≈√–∫∫  “√ π‡∑»

‡∑§‚π‚≈¬’) ·≈– ∂“π– ÿ¢¿“æ ¿“¬„μâ∫√‘∫∑∑“߇»√…∞°‘®

 —ߧ¡«—≤π∏√√¡Àπ÷Ëß

2.  ◊∫§âπÀ≈—°∞“π‡™‘ßª√–®—°…宓° PubMed, EMBASE, WEB of Science, Google, Google Scholar

·≈–μ‘¥μàÕ°—∫ √æ.§≈Õߢ≈ÿß √æ.°ßÀ√“ ·≈–√æ.æ—∑≈ÿß „π

∞“π–‡®â“¢Õß·À≈à߇հ “√∑’ˉ¡à “¡“√∂§âπæ∫∑“ßÕ‘π‡μÕ√å‡πÁμ

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°”·æ߇æ™√ ™–≈Õ °“√√—°…“ ∑¥·∑π‰μ ≈â“ß™àÕß∑âÕß øÕ°

‡≈◊Õ¥ º≈≈—æ∏å §√Õ∫§≈ÿ¡  ÿ¥∑⓬§◊Õ °√–∑”°“√ ◊∫§âπ·∫∫

snowball ®“°‡Õ° “√Õâ“ßÕ‘ß„π‡Õ° “√∑’˧âπæ∫¥â«¬«‘∏’°“√

‡À≈à“π—Èπ

3. ∑∫∑«π‡Õ° “√‡∫◊ÈÕßμâπ (scoping review) ‡æ◊ËÕ

§âπÀ“ª√–‡¥Áπ∑’Ë®”‡ªìπμâÕß ◊∫§âπ‚¥¬μ√ß/‡æ‘Ë¡‡μ‘¡®“°ºŸâ√—∫

º‘¥™Õ∫„πæ◊Èπ∑’Ë ·≈â«≈ßæ◊Èπ∑’Ë√«∫√«¡À≈—°∞“π‚¥¬°“√ª√–™ÿ¡

°≈ÿà¡ π∑π“À√◊Õ°“√ —¡¿“…≥åÕ¬à“߉¡à‡ªìπ∑“ß°“√ (focus group discussion or informal interviews) ·≈–°“√ —߇°μ (direct observation) æ◊Èπ∑’Ë≈– 1 «—π∑”°“√ §√Õ∫§≈ÿ¡

∫ÿ§§≈„πæ◊Èπ∑’ˇªÑ“À¡“¬ ¥—ßπ’ȧ◊Õ ºŸâ√—∫º‘¥™Õ∫®—¥∫√‘°“√∫”∫—¥

∑¥·∑π‰μ ‰¥â·°à ºŸâÕ”π«¬°“√ 欓∫“≈ ‡¿ —™°√ π—°

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4. ∑∫∑«π·≈–°≈—Ëπ°√Õß “√– ”§—≠®“°À≈—°∞“π‡™‘ß ª√–®—°…å ·≈–º≈°“√ —¡¿“…≥å/°“√ —߇°μ‚¥¬ºŸâ«‘®—¬®”π«π 2

§π‚¥¬„™âÀ≈—°°“√/·π«∑“ßμàÕ‰ªπ’È

°) «‘‡§√“–Àå°√≥’»÷°…“„π∫√‘∫∑μà“ßÊ ‡æ◊ËÕÀ“§«“¡

‡¢â“„®√à«¡°—π (common ground) √–À«à“ߺŸâ«‘®—¬‚¥¬§”π÷ß∂÷ß Õߧåª√–°Õ∫¢Õß√–∫∫ ÿ¢¿“æμ“¡°√Õ∫·π«§‘¥ çhealth sys- tems building blocksé

¢) «‘‡§√“–ÀåÀ“§«“¡‡™◊ËÕ¡‚¬ß §«“¡‡À¡◊Õπ·≈–

§«“¡μà“ß√–À«à“ß°√≥’»÷°…“ ‚¥¬æ¬“¬“¡∏”√ß√—°…“§«“¡

 ¡∫Ÿ√≥å (richness) ·≈–‡Õ°≈—°…≥å (uniqueness) ¢Õß

·μà≈–°√≥’»÷°…“ Õ—π®–‡æ‘Ë¡‚Õ°“ °“√¡Õ߇ÀÁπ·∫∫·ºπÀ√◊Õ

§ÿ≥≈—°…≥–∑’ˉ¡à‡§¬ª√“°Ø¡“°àÕπ (emerging themes/un- foreseen discoveries) ´÷Ëß¡’§«“¡ ”§—≠¬‘Ë߬«¥μàÕ°“√

∫√√≈ÿ«—μ∂ÿª√– ß§å‚¥¬‡©æ“–¢âÕ 3

§)  —߇§√“–Àå¢âÕ‡ πÕ·π–‡æ◊ËÕ°“√¢¬“¬º≈ (up- scale) √–¥—∫æ◊Èπ∑’Ë/ ∂“π欓∫“≈·≈–√–¥—∫π‚¬∫“¬ π—Ëπ§◊Õ æ¬“¬“¡μÕ∫§”∂“¡«à“  à«π„¥/≈—°…≥–„¥¢Õߧ«“¡ ”‡√Á®∑’Ë

¢¬“¬º≈‰¥â‡©æ“–æ◊Èπ∑’ËÀ√◊Õ√–À«à“ßæ◊Èπ∑’Ë ·≈–Õ–‰√§◊Õªí®®—¬

·Ààߧ«“¡ ”‡√Á® ‚¥¬ (°) ‰¡à®”‡ªìπμâÕßÕ“»—¬π‚¬∫“¬ π—∫ πÿπ (¢) ®”‡ªìπμâÕßÕ“»—¬π‚¬∫“¬ π—∫ πÿπ (·≈–π‚¬∫“¬π—ÈπÊ §◊Õ Õ–‰√)

ß) °√≥’¡’§«“¡‡ÀÁπμà“ß„πª√–‡¥Áπ °) - §) ‰¥â ª√÷°…“ºŸâ«‘®—¬§π∑’Ë “¡ ‡æ◊ËÕÀ“¢âÕ¬ÿμ‘‚¥¬„™â§«“¡‡ÀÁπæâÕß Õß

„π “¡

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∫√‘∫∑‡©æ“–¢Õßæ◊Èπ∑’Ë (contexts)

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‡»√…∞°‘®¥’°«à“ √æ.¡’¢π“¥„À≠à°«à“·≈–ºŸâ∫√‘À“√¥”√ß μ”·ÀπàßμàÕ‡π◊ËÕß¡“¬“«π“π°«à“°√≥’°ßÀ√“

∑’Ë¡“¢Õß°“√æ—≤π“∫√‘°“√‚√§‰μ‡√◊ÈÕ√—ß

°√≥’§≈Õߢ≈ÿß „πªï æ.».2540 ‰¥â√—∫°“√‡ πÕ«à“®–

∫√‘®“§‡§√◊ËÕß hemodialysis ·≈–®–„Àâ∑ÿπ àß欓∫“≈‰ª Õ∫√¡¥â“π hemodialysis ®”π«π 4 §π ®“°¡Ÿ≈π‘∏‘‚√§‰μ

·Ààߪ√–‡∑»‰∑¬ ·μàªØ‘‡ ∏ ‡æ√“– 1.¿“√–ß∫ª√–¡“≥

2.¢“¥·§≈π欓∫“≈ 3.‰¡à¡’·æ∑¬åÕ“¬ÿ√°√√¡‡©æ“–∑“ß ·≈–

4.√æ.‡πâπ∫√‘∫∑°“√ªÑÕß°—π à߇ √‘¡ ÿ¢¿“æ·≈– secondary medical care ¡“°°«à“ ·μàμàÕ¡“‡¡◊ËÕªï æ.». 2552 ¿“¬À≈—ß

°“√®—¥μ—Èß¡Ÿ≈π‘∏‘¿Ÿ¡‘√“™π§√‘π∑√å ‰¥â¡’°“√ª√—∫„Àâ¡’°“√™–≈Õ

‰μ‡ ◊ËÕ¡μ√ß°—∫∫√‘∫∑ √æ.§≈Õߢ≈ÿß ®÷߉¥â‡¢â“√à«¡¡◊Õ¥”‡π‘πß“π

°√≥’æ—∑≈ÿß/°ßÀ√“ ‡√‘Ë¡®“°·æ∑¬å‡©æ“–∑“ߥâ“π‚√§‰μ„π

√æ.æ—∑≈ÿ߉¥â√à«¡¡◊Õ°—∫À—«Àπâ“∑’¡æ¬“∫“≈‡«™ªÆ‘∫—μ‘„π

√æ.°ßÀ√“‡æ◊ËÕÀ“∑“ßÕÕ°„Àâ°—∫§ÿ≥¿“æ∫√‘°“√ºŸâªÉ«¬‡√◊ÈÕ√—ß∑’Ë

∂¥∂Õ¬‡æ√“–¡’¿“√–ß“π¡“° ‚¥¬¥”‡π‘π°“√√à«¡°—∫π‚¬∫“¬

°“√æ—≤π“°“√¥Ÿ·≈ºŸâªÉ«¬‚√§‰μ‡√◊ÈÕ√—ߢÕß®—ßÀ«—¥ (‚ª√¥

 —߇°μ«à“ ·æ∑¬å‡©æ“–∑“ߥâ“π‚√§‰μ∑’Ë°≈à“«∂÷߇ªìπ Õ“¬ÿ√·æ∑¬å∑’˺à“π°“√Õ∫√¡‡√◊ËÕß hemodialysis ‡ªìπ‡«≈“ 4

‡¥◊Õπ ·≈–ºà“π°“√Õ∫√¡‡√◊ËÕß peritoneal dialysis ‚¥¬μâÕß

√—∫º‘¥™Õ∫ß“π‚√§‰μ¢Õß√æ.æ—∑≈ÿß ∑—Èßπ’È ¿“¬„π®—ßÀ«—¥π’Ȭ—ß

‰¡à¡’Õ“¬ÿ√·æ∑¬å‚√§‰μ‚¥¬μ√ß)

Õߧåª√–°Õ∫¢Õß√–∫∫∫√‘°“√ ÿ¢¿“æ

„π‡°◊Õ∫∑ÿ°Õߧåª√–°Õ∫ §≈Õߢ≈ÿß‚¡‡¥≈¡’§«“¡

μ“√“ß∑’Ë 1 ¢âÕ¡Ÿ≈æ◊Èπ∞“π¢Õßæ◊Èπ∑’Ë«‘®—¬

ª√–‡¥Áπ °ßÀ√“ §≈Õߢ≈ÿß

ª√–™“°√ 35,833 §π 72,444 §π

140 §π μàÕ μ√.°¡. 92.48 §π μàÕ μ√.°¡.

„π 5 μ”∫≈ 45 À¡Ÿà∫â“π 4 ‡∑»∫“≈ 1 Õ∫μ. „π 10 μ”∫≈ 101 À¡Ÿà∫â“π 4 ‡∑»∫“≈ 9 Õ∫μ.

‡»√…∞°‘® GPP 2013 ®—ßÀ«—¥æ—∑≈ÿß 65,433 ∫“∑μàÕÀ—«μàÕªï GPP 2013 ®—ßÀ«—¥°”·æ߇æ™√ 159,906 ∫“∑μàÕÀ—«μàÕªï

≈—°…≥–™ÿ¡™π ª√–‡æ≥’‡≈’ȬßπÈ”™“‡ªìπ‚Õ°“ „Àâ √æ.°ßÀ√“√–¥¡ ‚√ßß“π‡§√◊Õ‡∫’¬√å™â“߇ªìπ‡ß◊ËÕπ‰¢„Àâ √æ.§≈Õߢ≈ÿ߉¥â√—∫

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‡§√◊Õ¢à“¬™ÿ¡™π ‚¡‡¥≈

∑√—欓°√„π™ÿ¡™π/ 1. √æ.°ßÀ√“‡ªìπ √æ.·Àà߇¥’¬«„πÕ”‡¿Õ ¢π“¥ 1. √æ.§≈Õߢ≈ÿ߇ªìπ √æ.·Àà߇¥’¬«¢ÕßÕ”‡¿Õ‡™àπ°—π ¡’¢π“¥

√–∫∫∫√‘°“√ ÿ¢¿“æ  “¡ ‘∫‡μ’¬ß∑’Ë®—¥Õ¬Ÿà„πæ◊Èπ∑’Ë°—π¥“√ 90 ‡μ’¬ß (F1)

„πæ◊Èπ∑’Ë 2. ·æ∑¬åÀ¡ÿπ‡«’¬π®”π«π¡“° ( ∂‘μ‘Õ“¬ÿß“π 2. ·æ∑¬åÀ¡ÿπ‡«’¬ππâÕ¬°«à“ (ºŸâÕ”π«¬°“√¥”√ßμ”·Àπàß

¢Õß ºÕ. ‰¡à‡°‘π “¡ªï) ¡“μàÕ‡π◊ËÕß°«à“ 20 ªï)

3. ¿“√–ß“π∫√‘°“√ºŸâªÉ«¬„π¥â«¬Õ—μ√“§√Õß‡μ’¬ß 3. §âπÀ“ DM/HT √à«¡°—∫‚√§‰μ‡√◊ÈÕ√—ß ‰¥âπâÕ¬°«à“

54% ‚¥¬≈à“ ÿ¥ ¡’§à“ CMI 0.46 (67.3-88.2% °√≥’Õ”‡¿Õ ·≈– 79.9%  ”À√—∫ √æ.)⁽¹⁸⁾ 4. ∫√‘°“√‚√§‡√◊ÈÕ√—ߥ⫬°“√ screen DM/HT

‰¥â§√Õ∫§≈ÿ¡ 94% HT admission 1.19 ‡∑à“

(target <1.00 ‡∑à“)⁽¹⁶⁾

5. ∑—ÈßÕ”‡¿Õ°ßÀ√“ “¡“√∂§âπÀ“ DM/HT √à«¡

°—∫‚√§‰μ‡√◊ÈÕ√—ß ‰¥â 70.2-87.7% (83.5%

„π à«π¢Õß √æ.°ßÀ√“)⁽¹⁷⁾

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eGFR 15-59 ml/min/1.73 m² 2). ®—¥∫√‘°“√‚¥¬∑’¡ À«‘™“™’æª√–°Õ∫¥â«¬·æ∑¬å‡«™ªØ‘∫—μ‘∑—Ë«‰ª, 欓∫“≈, ‡¿ —™°√, π—°°“¬¿“æ∫”∫—¥·≈–π—°

‚¿™π“°√√«¡ 5 §π ´÷Ëß∑ÿ°§πºà“π°“√Ωñ°Õ∫√¡‚¥¬∑’¡π—°«‘™“°“√¢Õß ¡“§¡‚√§‰μ¡“‡√’¬∫√âÕ¬ 3). ®—¥√–∫∫§≈‘π‘°„Àâ∫√‘°“√ 3 «—π/ —ª¥“Àå ¥Ÿ·≈ºŸâ ªÉ«¬«—π≈–ª√–¡“≥ 50 §π ·μà≈–§πμâÕ߇¢â“§≈‘π‘° 6 §√—Èß/ªï‡æ◊ËÕ√—∫§«“¡√Ÿâ 6 À—«¢âÕ §◊Õ §«“¡√Ÿâ∑—Ë«‰ª‡°’ˬ«°—∫‚√§‰μ, ‚¿™π∫”∫—¥ ”À√—∫‚√§‰μ‡√◊ÈÕ√—ß,

‚√§§«“¡¥—π‚≈À‘μ Ÿß, ‚√§‡∫“À«“π, °“√„™â¬“∑’Ë∂Ÿ°μâÕß ·≈– °“√√—°…“∑¥·∑π‰μ 4). ®—¥μ“√“ß„π§≈‘π‘°‚¥¬·μà≈–§√—Èß„™â‡«≈“ 60 π“∑’ æ∫ À

«‘™“™’æ∑ÿ°§π ·∫à߇ªìπæ∫欓∫“≈‡æ◊ËÕμ√«®√à“ß°“¬´—°ª√–«—쑇∫◊ÈÕßμâπ 5 π“∑’, ¥Ÿ«‘¥‘‚Õ‡√◊ËÕ߉μ 15 π“∑’, æ∫π—°‚¿™π“°√√—∫§«“¡√Ÿâ‡√◊ËÕßÕ“À“√ 15 π“∑’, æ∫‡¿ —™°√√—∫§«“¡√Ÿâ‡√◊ËÕ߬“ 10 π“∑’, æ∫π—°°“¬¿“æ∫”∫—¥√—∫§«“¡√Ÿâ‡√◊ËÕß°“√ÕÕ°°”≈—ß°“¬ 10 π“∑’ ·≈–æ∫·æ∑¬å‡æ◊ËÕ·®âߺ≈°“√™—π Ÿμ√

·≈–μ√«®√—°…“ —Ë߬“ 5 π“∑’ 5). ®—¥μ“√“ßμ√«®‡≈◊Õ¥°—∫ªí  “«–μ“¡·π«∑“ß°“√¥Ÿ·≈ºŸâªÉ«¬‰μ‡√◊ÈÕ√—ß∑’Ë ¡“§¡‚√§‰μ·Ààߪ√–‡∑»‰∑¬°”Àπ¥ªï≈– 2

§√—Èß°àÕπ·≈–À≈—߇¢â“√—∫∫√‘°“√ ‚√§√à«¡Õ◊ËπÊ ‡™àπ ‡∫“À«“π„Àâ√—∫°“√μ√«®™—π Ÿμ√‡æ‘Ë¡‡μ‘¡μ“¡·π«∑“ߢÕß‚√§π—ÈπÊ⁽⁸⁾ 6). ®—¥‡°Á∫¢âÕ¡Ÿ≈∫—π∑÷°°“√μ√«®

√—°…“ºŸâªÉ«¬∑ÿ°§π¥â«¬√–∫∫§Õ¡æ‘«‡μÕ√å„π§≈—ߢâÕ¡Ÿ≈ ·≈– ”√ÕߢâÕ¡Ÿ≈„π§Õ¡æ‘«‡μÕ√å¢Õߧ≈‘π‘°™–≈Õ‰μ‡ ◊ËÕ¡·¬°μà“ßÀ“°

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- °”À𥧫“¡∂’Ë„π°“√‡¬’ˬ¡∫â“π™—¥‡®π

- °“√§—¥°√Õß‚√§‰μ‡√◊ÈÕ√—ß®”°—¥‡©æ“–ºŸâªÉ«¬‡∫“À«“𠧫“¡

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- ‡¿ —™°√

- System manager - CKD nurse

- ∫ÿ§≈“°√ª√–®” √æ μ. 1 §π ·≈– Õ ¡. 3-5 §π„π·μà≈–

μ”∫≈

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